introduction to methods of research

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Methodology

Research Methods | Definition, Types, Examples

Research methods are specific procedures for collecting and analysing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

Qualitative vs quantitative : Will your data take the form of words or numbers?
Primary vs secondary : Will you collect original data yourself, or will you use data that have already been collected by someone else?
Descriptive vs experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyse the data .

For quantitative data, you can use statistical analysis methods to test relationships between variables.
For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Methods for collecting data, examples of data collection methods, methods for analysing data, examples of data analysis methods, frequently asked questions about methodology.

Data are the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .


Qualitative
Quantitative		.

You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.

Primary vs secondary data

Primary data are any original information that you collect for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary data are information that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data. But if you want to synthesise existing knowledge, analyse historical trends, or identify patterns on a large scale, secondary data might be a better choice.


Primary
Secondary

Descriptive vs experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.


Descriptive
Experimental

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Research methods for collecting data
Research method	Primary or secondary?	Qualitative or quantitative?	When to use
	Primary	Quantitative	To test cause-and-effect relationships.
	Primary	Quantitative	To understand general characteristics of a population.
Interview/focus group	Primary	Qualitative	To gain more in-depth understanding of a topic.
Observation	Primary	Either	To understand how something occurs in its natural setting.
	Secondary	Either	To situate your research in an existing body of work, or to evaluate trends within a research topic.
	Either	Either	To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study.

Your data analysis methods will depend on the type of data you collect and how you prepare them for analysis.

Data can often be analysed both quantitatively and qualitatively. For example, survey responses could be analysed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that were collected:

From open-ended survey and interview questions, literature reviews, case studies, and other sources that use text rather than numbers.
Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions.

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that were collected either:

During an experiment.
Using probability sampling methods .

Because the data are collected and analysed in a statistically valid way, the results of quantitative analysis can be easily standardised and shared among researchers.

Research methods for analysing data
Research method	Qualitative or quantitative?	When to use
	Quantitative	To analyse data collected in a statistically valid manner (e.g. from experiments, surveys, and observations).
Meta-analysis	Quantitative	To statistically analyse the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner.
	Qualitative	To analyse data collected from interviews, focus groups or textual sources. To understand general themes in the data and how they are communicated.
	Either	To analyse large volumes of textual or visual data collected from surveys, literature reviews, or other sources. Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words).

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Chapter 1: Introduction to Research Methods

Learning Objectives

At the end of this chapter, you will be able to:

Define the term “research methods”.
List the nine steps in undertaking a research project.
Differentiate between applied and basic research.
Explain where research ideas come from.
Define ontology and epistemology and explain the difference between the two.
Identify and describe five key research paradigms in social sciences.
Differentiate between inductive and deductive approaches to research.

Welcome to Introduction to Research Methods. In this textbook, you will learn why research is done and, more importantly, about the methods researchers use to conduct research. Research comes in many forms and, although you may feel that it has no relevance to you and/ or that you know nothing about it, you are exposed to research multiple times a day. You also undertake research yourself, perhaps without even realizing it. This course will help you to understand the research you are exposed to on a daily basis, and how to be more critical of the research you read and use in your own life and career.

This text is intended as an introduction. A plethora of resources exists related to more detailed aspects of conducting research; it is not our intention to replace any of these more comprehensive resources. Feedback helps to improve this open-source textbook, and is appreciated in the development of the resource.

Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Social Science Research: Principles, Methods and Practices - (Revised edition)

(43 reviews)

Anol Bhattacherjee, University of South Florida

ISBN 13: 9781475146127

Publisher: University of Southern Queensland

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Kelle DeBoth Foust, Associate Professor, Cleveland State University on 6/22/23

Comprehensiveness rating: 5 see less

The text really seems to do as it claims; provides the basic overview of the research material needed for graduate students without a lot of other “fluff.” It’s written very clearly, easy to understand and many figures and charts that enhance learning. It covers the majority of the topics that I need it to cover for OTH 740/Research I, at about the level of detail that the students should be able to digest. In particular, I like the sections on survey research, experimental research and that it covers quantitative and qualitative analyses.

Content Accuracy rating: 4

As far as I can tell reading through it, the content is accurate and unbiased (will be able to review further once actually implemented in the intended course).

Relevance/Longevity rating: 4

The content is current at least regarding how we continue to teach and use it in our field. Some of the references are a little outdated, although not much has changed in this world in recent years. I also recognize I can pull more recent literature in order to make the examples up to date and relevant for my particular students.

Clarity rating: 5

This book is written very clearly. I feel that the diagrams really help to add and make sense of higher level concepts that students may struggle with. Concepts that are challenging are recognized as such within the text, with appropriate examples that enhance clarity (will be able to review further once actually implemented in the intended course)

Consistency rating: 5

Yes, the text appears to be internally consistent in terms of terminology and framework.

Modularity rating: 5

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader. – Yes. The division of the content makes sense, and how smaller modules are paired (e.g., qualitative and quantitative analysis paired back to back) is logical to facilitate learning.

Organization/Structure/Flow rating: 5

The text and chapters are laid out in an order that makes sense and provides good flow and continuity between the concepts and analytical applications. In particular, I like how research is introduced, moving into research design and then analysis all within the same text. Will make this more manageable for students.

Interface rating: 5

The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader. – Very well put together, no issues with the interface. I would consider this to be very user/student friendly. In particular, the authors made a point to keep it “short and sweet” so students should not be intimidated by the length of the chapters (which is excellent for helping to convince the students to actually read them).

Grammatical Errors rating: 5

The text contains no grammatical errors. – None detected.

Cultural Relevance rating: 5

The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds. – No offensive content noted, the majority of the examples used do not have cultural significance and therefore the amount of diversity is sufficient.

This review was written based on a preliminary review of the text prior to use and implementation within the intended course. I will update the review if it significantly differs once students have used it for their course study.

Reviewed by Ingrid Carter, Professor, Metropolitan State University of Denver on 4/14/23

The textbook includes many of the important elements of a foundational social science research course. A key element of the course I teach which is not included in the text is how to search for literature to inform the research, how to synthesize... read more

Comprehensiveness rating: 4 see less

Content Accuracy rating: 3

The content appears to be mostly accurate and unbiased. There is a large emphasis on positivist approaches, and more post-positivist and innovative research approaches should be added to the content.

The text is relevant to foundational/introductory social science research courses. As mentioned previously, broader and more diverse perspectives of research are missing.

Clarity rating: 4

The content is presented clearly.

Consistency rating: 4

The text is presented with a consistent framework and format. The variety of frameworks included could be greater, with at minimum a presentation of different research paradigms and ideally with discussion or questions to grapple with related to various research paradigms and approaches.

As the author indicates, the textbook consists of 16 chapters which can be used in a 16-week semester. These can be easily assigned for weekly readings.

The textbook is well-organized.

Interface rating: 4

The interface is relatively clear

No grammatical errors were found in my initial review. I have not yet used the textbook for the course I am teaching, and therefore have not reviewed the textbook page by page nor line by line.

Cultural Relevance rating: 3

More diverse and culturally relevant example to a diverse audience could be embedded. I did not encounter offensive material.

Reviewed by Sanaa Riaz, Associate Professor, Metropolitan State University of Denver on 3/27/23

Comprehensiveness rating: 3 see less

While not meant for advanced graduate and doctoral students, this text is an excellent introductory resource for learning about paradigms in research methods and data analysis and prepares the learner to begin writing a successful research project proposal. The text largely privileges the scientific method and labels diverse social science research methods as such. However, the preparatory considerations in beginning social science research have been discussed. The book contains important terms in bold to guide a beginner reader as well as sample syllabi for incorporating it at the graduate level. However, the text could be made more comprehensive with the inclusion of an effective index and/or glossary.

Content Accuracy rating: 5

The text is a quick guide to considerations and terminologies used in social science research. The content is accurate, error-free and unbiased.

The text provides a basic introduction to research methods in the social sciences. Updates in social science inquiry with respect to social media and popular culture platforms and mixed methods research should be easy to incorporate.

The text has been written from the point of view of a non-expert. It is free of technical jargon and is meant to provide the essentials of social science inquiry and research considerations.

Consistency rating: 3

The text is internally consistent in terms of terminology within a chapter section. However, it is strongly recommended that the framework is revisited for chapters discussing qualitative research methods and approaches. Qualitative data analysis has not been explored in depth and the basic framework for Chapter 13 will need to be substantially expanded to provide for a smoother transition from a discussion on grounded theory to content analysis and hermeneutic analysis and to incorporate information on other analyses undertaken in qualitative research.

Chapters and sections in the text can be easily reorganized and assigned as per needs of the instructor and the course without causing disruption to the reader.

Organization/Structure/Flow rating: 3

Chapter sections of the book covering qualitative research are not presented in a logical manner. It is highly recommended that the readers are told about the place of exploratory and other research in social science research inquiry, rather than labeling them as scientific research. Moreover, mixed methods and qualitative visual and social media platform research needs to be discussed. The book overall shies away from delving into approaches and methods in non-empirical research in the social sciences.

The text is easy to navigate. All words, sections and tables are easily searchable.

The book is free of grammatical errors.

The text does not contain any culturally insensitive information as there are hardly any research project examples incorporated.

Incorporating examples and case studies across social science disciplines (after introducing the disciplines in which social science research is employed in the first chapter) would allow readers to see the applicability of one social science research approach, method and data analysis over another based on the research project focus.

Reviewed by Cahit Kaya, ASSISTANT PROFESSOR, University of Texas Rio Grande Valley on 10/17/22

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55. read more

Comprehensiveness rating: 2 see less

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55.

IT SEEMED ACCURATE

Relevance/Longevity rating: 3

IT IS RELEVANT

IT IS CLEAR

IT IS CONSISTENT

Modularity rating: 3

IT NEEDS MORE MODULES

Organization/Structure/Flow rating: 2

IT CAN BE OGRANIZED BETTER

YES BUT EVEN THOUGH IT CAN BE IMPROVED

Grammatical Errors rating: 4

I DID NOT SEE IT

MORE CULTURAL DIVERSE EXAMPLES CAN BE GIVEN

Reviewed by Dawn DeVries, Associate Professor, Grand Valley State University on 12/9/21

The text provides a complete summary of the research process. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science fields. Two areas could be more in-depth, specifically the IRB discussion and the chapter on surveys. Information provided is accurate and succinct as the author intended, providing a comprehensive overview of the research process.

The content is accurate and presented in an objective manner. There was no perception of bias or conflict that would impact accuracy. The chapters offer a variety of examples, inclusive of a variety of social science fields.

Written in 2012, the information remains relevant with few areas that would ever need to change. The research process and research methods stay fairly consistent with little variation; thus, the text would not need regular updating. Updates, if and when needed, would be easy to implement due to the concise and objective writing and the logical organization of the textbook. One area needing updating (or that instructors would need to supplement) is Chapter 9 on Survey Research. The chapter refers to mail surveys, which in 2021, are almost obsolete. Little is presented or discussed on electronic surveys, survey platforms, or the use of social media in recruitment, survey distribution or every survey completion. Furthermore, there is no mention of the ethical issues related to social media research.

Key terminology is bolded with the definition following, making it easy to identify. Definitions are clear and adequate to facilitate understanding of the concepts and terms. The text presents the research process in a logical and understandable way using scaffolding.

The chapter structure, framework, and style are consistent.

Modularity rating: 4

The chapters provide easily divisible readings of 8-10 pages. The chapters are ordered in a logical fashion and flow easily, yet they could be rearranged to fit instructor preferences for order. Chapters are concise, allowing the combination of multiple chapters for a week’s reading if needed. The text is designed for a 16-week semester, but again, because the chapters are not long, several chapters could be read as one assignment. It would be difficult to reduce chapter readings (say, using only 5 pages of the chapter) because of the conciseness of the information and the shortness of the chapters.

The text is logical and has flow. It starts general (with How to Think Like a Researcher) and builds to specific, more detailed content (Inferential Statistics).

There are no observed problems with the interface of the text. Images used are clear and display without difficulty. No hyperlinks are used.

No observed issues or concerns related to grammar or mechanics.

No concerns about inclusivity or offensiveness. The text is clear and concise, offering a variety of short examples specific to various social science professions.

The text reminds me of my Research Methods textbook from my doctoral program. It addresses the differences between scientific research and social science methods in a clear and concise manner. While it is an overview of the information, it is specific and concise enough for students who need to understand the research process but won’t be engaging in research as their full-time profession. Content is brief in a few areas as mentioned, which will allow the instructor to provide supplemental reading or lecture content specific to the university (i.e., IRB) or to the profession. As the author suggests, certain chapters could be skipped depending on the program. For example, chapters 13 – 15 on statistics could easily be omitted if the program has a research statistics course. A nice add is the sample syllabus for a doctoral program.

Reviewed by David Denton, Associate Professor, Seattle Pacific University on 5/3/21

I use this book with graduate students in education taking an initial course in education research. Dr. Bhattacherjee notes the book is organized for semesters with supplemental readings, as shown by the sample syllabus in the appendix. Nevertheless, I have found the book is excellent in meeting objectives for an introductory course in education research, though it is necessary to add education context and examples. Some of the course objectives I have developed from the textbook include i) distinguishing between questionnaire survey method and interview survey method and ii) summarizing criteria for developing effective questionnaire items, among many others. There are some sections that exceed student knowledge without some background in statistics (e.g. description of factor analysis) but omitting these sections as required reading is easy since there are many subheadings used to segment chapters.

Dr. Bhattacherjee has done an excellent job of clearly communicating the content with accuracy. For example, the textbook distinguishes between qualitative and quantitative analysis (rather than qualitative and quantitative research, an appropriate distinction). The textbook makes other distinctions in a way that helps students comprehend concepts (e.g. survey interview and survey questionnaire). At the same time, the textbook does not over-emphasize research methods or design, which might mislead students to think inflexibly about the topic.

Relevance/Longevity rating: 5

One of the advantages of the book, in my view, is that it will not become obsolete anytime soon. It addresses all major topics of interest for instructors needing to develop student background knowledge in social science research methodology. For example, some topics for which the book provides helpful structure include i) Thinking Like a Researcher, ii) The Research Process, iii) Research Design, iv) and Sampling. In addition, an instructor can easily supplement or provide subject-specific examples where needed since the book is thoroughly segmented by chapter and chapter subheadings.

Dr. Bhattacherjee does a fine job of defining terms concisely. I do not recall use of jargon, or if there are complicated terms, the text provides enough elaboration so that students can at least attain a conceptual understanding. In some instances, definitions are so concise that I find it necessary to elaborate with examples. This, however, is a part of instruction and would be done in any case.

The textbook is highly coherent, in my view. Similar to modularity, consistency is a strength. For example, chapters are grouped into four sections: Introduction to Research, Basics of Empirical Research, Data Collection, and Data Analysis. Further, chapters within major sections are sequential, such as chapters on Science and Scientific Research, followed by Thinking Like a Researchers, followed by The Research Process. In addition, content within chapters is consistent, such as Dr. Bhattacherjee’s logical progression of concepts: empiricism, to positivism, to forms of analysis (qualitative and quantitative), etc

Modularity is one of the clear strengths, again in my view. From a structural perspective, neither the chapters nor subsections are very long because Dr. Bhattacherjee writes concisely. Both chapters and subordinate subsections lend themselves to various kinds of divisions. For example, students in need of supplemental instruction on descriptive statistics, such as content about the normal distribution, can be assigned the subsection on Statistics of Sampling in chapter 8, followed by the subsection on Central tendency in chapter 14. Some non-sequential reading is required if students do not have any background in statistics, but this is not difficult to manage using page numbers or subheadings as reference.

Organization/Structure/Flow rating: 4

The textbook is well organized. Nevertheless, there are some sections that I found helpful to have students read out of sequence. For example, there is a short section at the end of chapter 5, Scale Reliability and Validity, which is perhaps best read after students cover correlation and normal distribution, dealt with in chapter 14. Again, I did not find it difficult to assign sections out of sequence using either page numbers or chapter subheadings as reference.

The textbook does not have interface issues. Chapter titles are hyperlinked within PDF copies to simplify navigation. Some may judge a few of the images as low resolution, but if this is a defect it is not one that interferes with communicating concepts, which is the purpose of the images.

There are a few minor grammatical errors in the 2nd edition, 2012. For example, on p. 126, Dr. Bhattacherjee notes “five female students” when the Chi-square table appears to show four. This is minor, but if students are new to reading Chi-square tables they may not detect the error and believe interpreting a Chi-square table is different than interpreting a typical data table.

The textbook presents appropriate information without prejudice or unfairness. As mentioned, instructors will likely need to include examples that are specific to their course objectives and student populations. For example, chapter 11. Case Research provides exemplars that focus on business and marketing domains. This seems entirely appropriate given Dr. Bhattacherjee’s research area. Instructors using the text for other domains, such as education research, will be interested in elaborating on concepts using examples specific to the needs of their students.

I greatly appreciate that Dr. Bhattacherjee has shared his book as an Open Textbook.

Reviewed by Elizabeth Moore, Associate Professor, University of Indianapolis on 4/24/21

In Chapter 5 on Research Design there isn't any discussion on how to improve content and statistical conclusion validity. There isn't a discussion of threats associated with the four types of validity. The chapter also does not present how the research design and threats to validity are interconnected. There is a lack of comprehensiveness in the presentation of qualitative research as qualitative research rigor is not addressed.

The content is accurate, error-free, and unbiased. I would like more examples focused on social sciences. Some of the examples are related to business/industry. There are many social science examples that could be used.

Many of the examples should be updated. With everything that is (has been) happening in the U.S. and world, there are many examples that can come from the social sciences. For example, there are several examples that could represent the concept of technostress, especially with many professionals having to move into online environments. Students would be more likely to read assigned chapters and understand the material presented if the examples were relevant to their profession.

The book is clear and has high readability. There are several accessibility issues in the document. This should be checked and fixed. There are 5 issues in the document, 4 in tables, 5 in alternative text, etc. Accessibility is a big issue right now. All documents have to be accessible to all students.

While there is consistency within the textbook, in some topics there is a lock of consistency in how some of the terms and material relate to what is actually used in social science disciplines. For example, in basic social science textbooks in chapters presenting an introduction to measurement of constructs, descriptive statistics that are unfamiliar and rarely used, such as geometric mean and harmonic mean, should not be introduced. This information is usually difficult for novice researchers to understand without adding more advanced descriptive statistics.

It is confusing as to why research validity is in Chapter 5 - Research Design. There is not a discussion of how different research types are affected by different types and threats of research validity. The title of Chapter 7 is misleading. The word "scale" is associated with scale of measurement. It would be better to use designing measurement tools/instruments in the chapter name since the types of validity and reliability discussed are related to creating and developing measurement tools/instruments. I also think Chapter 6 - Measurement of Construction should not come before Chapter 7 - Scale Reliability and Validity since measurement of constructs and scale reliability and validity are related to qualitative research.

I like the organization. It follows the current syllabus I use so it will require very little modifications.

As mentioned below, bookmarks would improve navigation of the pdf file. Also, having links from the table of contents to chapters would be helpful. Including some of the important subsections of the chapters would also improve navigation of the pdf version of the book. Tables and charts are helpful and supplement the text. Use of images would break-up the text.

None were noted.

Cultural Relevance rating: 4

See comments above about the relevancy of the material. While it is important to make sure a book is culturally sensitive and not offensive, it is also important to not ignore what is known about social injustices which are well-documented. Look at the lack of diversity in many professions and organizations, this is important to address.

It would be helpful if bookmarks were placed in the pdf version. While this is a social science textbook, it would be helpful to have subsection in Chapter 4 that introduces at least a couple of the main health behavior theories. These are commonly used by many researchers in social sciences.

Reviewed by Barbara Molargik-Fitch, Adjunct Professor, Trine University on 3/6/21

This textbook provides a nice overview of several topics related to social science specific research. read more

This textbook provides a nice overview of several topics related to social science specific research.

The textbook seems to be accurate and error free.

The text seems to be accurate, relevant, and useful.

The text is organized well and had a professional and academic tone while also understandable.

Text seemed to be internally consistent.

Text is easily divisible to be assigned as different points within the course.

Text is well organized.

The text is free of significant interface issues that would distract or confuse the reader.

I did not see grammatical errors.

I did not see any cultural issues.

I will be using this textbook for one of my classes. I am looking forward to using it. I think it has a lot to offer students looking to develop their research skills.

Reviewed by Kenneth Gentry, Assistant Professor, Radford University on 6/2/20

This text provides a great overview of core concepts relevant to health-science research. An overview of theory, designs, sampling, data collection, data analysis, and ethics are provided. It may be helpful in future editions to add additional content relating to qualitative research (i.e. additional types of designs, as well as how trustworthiness and rigor are addressed [for example, what specific steps can be taken by researchers to address dependability, credibility, confirmability and transferability]).

Information presented appears accurate and unbiased.

While much of the content is 'durable' (not likely to soon become obsolete), the relevance is dependent upon the focus of the instructor/course. For example, if the emphasis of the course will be on quantitative research, then this text is highly relevant, however, if the emphasis is on an equal balance between the traditions of qualitative and quantitative, then this text is slightly less relevant due to the more limited nature of its content in qualitative (in comparison to content on quantitative). That is not to say that this text does not address content relevant to qualitative research, however, it does so with decidedly less depth and breadth than quantitative.

While a subjective interpretation of clarity is highly dependent upon the reader, I found this text to strike a good balance between a scholarly, academic tone, and commonly-understood, easily-relatable descriptions of key concepts. There were times where I wish that the latter had been more so, however, considering the target audience of this text, I feel that the author struck a good balance. Occasionally, there were concepts that I anticipated would require additional clarification (beyond the reading) for my graduate students.

Overall, I found the text to be generally consistent in its approach to the content. Occasionally, there were instances when the flow made sense at the chapter level, however, content might have been spread between chapters (i.e. theory is discussed in Chapters 1, 2 and 4).

This ties in with my comments on consistency. Since some concepts are discussed in more than one place, it might be difficult to identify a single reading for a specific topic ... one might need to assign several readings from more than one chapter. However, having said that, I anticipate that those instances would be infrequent. On the whole, the text demonstrates a fairly good degree of modularity.

At the chapter level (i.e. main topics), and within each chapter, information appears well organized. It is the appearance of content in multiple places that was occasionally problematic for me as I read (i.e. when reading about reliability and validity, I questioned why the author did not discuss the types of reliability and validity ... I later found that content in a subsequent chapter).

Interface rating: 3

While images were viewable, many appeared 'pixelated'/'grainy' (low resolution). This was more of a cosmetic issue, and did not affect the overall interpretation of the image.

Overall, the content was grammatically strong.

Content was not culturally insensitive or offensive.

My sincere thanks to this author, and to the Open Textbook Library and Scholar Commons for this text. I truly appreciate the investment of resources that were invested. I just completed instructing 2 semester courses on research in a graduate health science degree program ... I plan to adopt this text the next time I am rotated into those courses again!

Reviewed by Wendy Bolyard, Clinical Assistant Professor, University of Colorado Denver on 4/30/20

This text presents all the topics, and more, that I cover in my master's-level research and analytic methods course. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. I would have... read more

The concepts were presented accurately and often with citations.

The great thing about research methods is that the content ages well (does not change over time). The examples were relevant and should not make the text obsolete. Any instructor should be able to provide current, real-world examples to compare and contrast to those in the text. Although the sample syllabus if for a business class, I did not find the text to be relevant only to business students. The authors uses broad social science illustrations that cross disciplines. This text is definitely relevant to public affairs/public administration.

The text is well-written and provides clear yet concise context.

When students are learning a new language - research methods - they may be confused when definitions vary. Causality is explained with slightly different language which may be misunderstood by students.

One chapter includes a summary section. It would have been helpful to include a summary of key takeaways for each chapter, and perhaps include a list of key terms and definitions (since the text does not include a glossary).

The text follows the linear, systematic research process very well.

The font, size, and spacing varied in some sections. The images were a bit blurred.

A few typos, but otherwise well-written and very clear.

Culturally sensitive with relevant and inclusive cases provided.

I will be adopting this text to supplement other readings assigned in my master's-level research and analytic methods course. I appreciate the clear and helpful context it provides on key concepts that students must understand to become effective researchers. The text is comprehensive yet concise and would not overwhelm students.

Reviewed by Valerie Young, Associate Professor, Hanover College on 12/19/19

I really appreciate the broad focus and examples from social science fields. As a fellow social scientist from a high growth area (communication studies), I would appreciate even more breadth! I supplement with many field-specific resources, so this critique is very minor. An appropriate place and reference might be within the first chapter, under the heading Types of Scientific Research, to give a nod to some of the social science fields and the importance of interdisciplinary questions across disciplinary lines.

I did not find any errors in the content of the book. One critique is that the author rarely cites any sources for assertions or materials. I get the impression that the author is relying on "commonly known" ideas regarding research methods and processes, but I have to consistently remind my students to cite all non-original information, and that example is lacking in this text. As an example, regarding evaluating measurement scales for internal consistency, the author references commonly-accepted factor loadings (>.60) but does not reference or provide linked resources for readers to corroborate this or seek additional readings.

The text content is relevant and the author has taken care to provide relatively timeless sample research examples throughout. Some examples include areas of social and political interest (conflict, crime), business and marketing, and social psychology. The contents of the text are not dated and the author does a fantastic job of offering a variety of relevant examples so that readers of all backgrounds can relate to the content.

Incredibly clear and concise. Main ideas are clearly articulated in headings. Bullet point lists are used infrequently, but appropriately. The writing style is professional, academic in tone, yet relate-able. There is little, if any, discipline-specific references that a graduate student from any area of social sciences could not comprehend; however, this book is empirically-grounded and quantitatively focused. For our readers in fields with lower quantitative literacy, some of the terminology in chapters is better suited for students with basic statistical experience, some research methods or theory coursework completed.

This text is consistent and detailed in the use of interdisciplinary, social scientific terminology.

The layout of materials and the concise writing style contribute to an easy-to-visualize text. The page layout and brief chapters make it appropriate to assign supplemental readings along with the chapter topics. Some areas for improvement: use hyperlinks to reference forward and backward within the text so that readers can pop back and forth to related concepts. Include links in the text to reputable online materials or publications. See my comment below in Organization feedback concerning chapter ordering.

One thing that strikes me as amazing and also challenging about this text is the concision and simplicity for which Bhattacherjee integrates complex information. The chapters are very brief- about half of what would be a typical, field-specific textbook, but the content is simultaneously dense and clear. For example, Chapter 7 addresses scale reliability and validity. In just a few short pages, we get an incredible density of information and terminology, from a formula and brief explanation of Chronbach's alpha to exploratory factor analysis as a method to demonstrate convergent and discriminant validity. There is an appropriate number of tables to visually demonstrate complex topics in-text. Overall, the chapters are well-organized and easy to follow with a working knowledge of basic stats. The introductory chapters have been intentionally placed to introduce readers to basic principles. The following chapters could be assigned as readings in any order that fit with the student's needs (but I find the order of these chapters appropriate, as-is): Chapter 9 Survey Research, Chapter 10 Experimental Research, Chapter 11 Case Research, Chapter 12 Interpretive Research, Chapter 13 Qualitative Analysis, Chapter 14 Quantitative Descriptive Statistics, Chapter 15 Quantitative Inferential Statistics. The final chapter, 16, covers Research Ethics, which seems to have been lopped on at the end of the text. It would be a better fit in the first third; perhaps integrated into one of the first several chapters with a nod toward the evolution of social research.

Regarding navigation, the pdf online version does not allow for creative navigation through the document. Graphics and charts are clear and easy to see in the online pdf version. They are a little smaller than I would like on the page, but the text is clear and the tables and graphs are visually appealing. It looks like most of the graphics were created using PowerPoint. One odd thing I noticed is that the paragraph spacing is inconsistent. In one section, the spacing between paragraph lines seems to be set at 1.25, and then, for no apparent reason, the line spacing moves back to single space. This is not visually distracting, just peculiar. Overall, the graphics in the online version are much clearer than in the softcover print version, which prints only in greyscale, with quite a bit of granulated distortion in the figures.

I did not notice any writing errors.

The research topic examples represented a diverse array of research topics, methods, fields, etc. The overview of science, scientific research, and social science was welcomed and unique to this text. Some areas for improvement would be to include historical scientific figures who are not all male, and link critical methodology in a clearer manner with specific critical and cultural examples of this form of research.

Reviewed by Lee Bidgood, Associate Professor, East Tennessee State University on 10/29/19

The text seems comprehensive, covers a wide range of research approaches, and parts of the research process. I will have to supplement with more of the area-specific writing that my students need, but this is easily added in the adapted version... read more

This text seems to follow the path of other texts that outline research design and methods, such as the Creswell book that I have used for several semesters. I do not detect bias in the text, or any significant errors.

I will discuss disciplinary relevance rather than chronological applicability (which other reviewers have already addressed thoroughly). The course for which I seek a textbook is meant to prepare students in a non-discipline-specific regional studies context, and for a range of methodologies and research design possibilities, mostly in the social sciences and humanities. This text is most relevant to the potential research programs of our students in discussions of the precursors to research design in Chapter 2 (“Thinking like a researcher”) and of the using and creating of theory in Chapter 4 (“Theories in Scientific Research”).

The authors’ prose is clear and easily comprehensible. Definitions are clear, and sufficient (jargon is explained). There could be more examples to clarify and assure comprehension of concepts, I plan to add these in my adaptation.

There is not an overt intra-chapter organization scheme that is consistent from chapter to chapter--each chapter differs in the sorts of content, that some sort of generic outline would feel forced, I think. The “feel” of the text, though, is consistent, and effectively conveys the content.

Because it uses footnote citations instead of endnotes / parenthetical citations, each page contains all of the references contained on it, which helps with modularity. The portions of the text that are less relevant to the course I teach (i.e. the more technical and statistical chapters, such as Chapters 6, 7, 8, 14, and 15 are easily omitted; I will be able to adapt portions of this text (i.e. the discussion of sampling in Chapter 8) without needing to provide all of the chapters. Some of the more technical vocabulary will require editing and explanation, but this seems manageable for me as an adapter.

The book is logically organized and the topics make sense in the order presented. I agree with another reviewer that the ethics portion seems like an appendix, rather than an essential and structural part of the book. As I adapt this text, I would address ethics at the beginning (as I do in my current teaching of research methods) and infuse the topic through other sections to address ethics-related concerns at all stages of research design and implementation. The author’s choice to use footnotes for references is not the one that seemed logical to me at first - it seems “elegant” to put all the references in a list at the rear of a book; now, reading through the whole text, however, I see some value to having the entirety of a citation at hand when reading through the main body of the text. Still, I miss the comprehensive list of works cited at the end of the book, which I would add to a text that I create, since an e-text is not limited by the economics of physically-printed books.

The text is workable as presented in the PDF document that I downloaded. Charts and other imagery are usable. There are no extra navigation features (a link to take a reader to the table of contents in a header or footer, etc.). I am left wondering if, in a PDF form, an OER textbook would be more useful with more navigation features, or if they might make the document buggy, cluttered, or otherwise affect use.

I did not detect any issues with grammar, usage, etc. in the text.

There is a lack of specific examples that might lend a sense of wide scope / global appeal to the textbook, and create an inclusive atmosphere for a reader/student. The author has stated that they hope to translate and widely distribute the text - perhaps, as is the case in the syllabus that the author provides, the hope is that in use for a course, additional readings will provide local knowledge and place-, culture-, and discipline-specific details and context.

This is a solid text that will provide a framework for adaptation in another disciplinary / area context.

Reviewed by Kevin Deitle, Adjunct Associate Professor, TRAILS on 10/6/19

I am pleased with the coverage in the text; it includes the history and foundations of research, as well as chapters on ethics and a sample syllabus. The structure and arrangement of the book differs from my own understandings of research and how I present it in class, but all the material covered in my class appears in the text, and it can be ordered to fit my syllabus. This text spends more time with statistics than I include in a research course, but again, that can be omitted or just used for reference. The book does not include either an index or a glossary, which is unfortunate for anyone who wants a paper version. Of course, most students seem to prefer an electronic text, so I assume they use a search function rather than an index.

I have not spotted any glaring errors, other than an occasional grammatical slip or a cumbersome edit. The author includes a few citations, usually following APA style, but employs footnotes instead of a reference section. The content mostly aligns with my own conceptions of research, although it does have a different arrangement from my presentation in class. This does not suggest that the content is wrong, only that I would likely rearrange it to suit my instructional sequence. I sense no bias in the presentation, including the historical or ethical portions, or sections that mention religion. I’m comfortable that I could rely on this book in class without worrying over slanted content or editorialization.

Research is something of a traditional topic, in the sense that changes or evolutions move at a comfortably slow pace. I expect there is very little of this text that is likely to become obsolete any time soon. The flip side is there is little in this book that is necessarily cutting-edge, but that is not the fault of the author at all. And in the unforeseeable situation where a new protocol or a new advance in either statistics or research warrants an update, I think the organization and the modular design will allow that to happen without major upheavals in the structure or arrangement of the text.

As mentioned elsewhere, the writing is comfortably academic without becoming dense or burdensome. I have seen introductions to research that were more casual and probably fit a beginner audience better than this would, but I daresay this is intended as a core text for a graduate-level class, and for that reason, can be expected to sound less approachable and more authoritative. The text employs features for fast visual reference, to include breaks in the text to allow for visual elements, and bolded text where key terms are introduced or defined. While this would probably not be a particularly exciting text for a self-study course, it will sit well with classes that need a reference text that takes the time to explain concepts with some authority.

Structurally the author has a style and sticks to it throughout the text. Visually this book is sparse, and it will require some effort on the part of the professor to make the content digestible in a classroom environment. However, that also suggests that the arrangement and format remain predictable from the first page to the last, without any surprises in presentation or discourse. Research has a tendency to step on its own toes when it comes to terminology, but this text follows those conventions for the most part, making it mostly congruent with other research texts I have seen. I think this book would complement other research texts without causing too many difficulties in terminology or arrangement.

The author suggests in the preface that the work was intended to be rearranged by sections, and I can appreciate how the chapters and structure support that statement. I do see this more as a foundational reference for a graduate-level course than a self-study text though, and it has the feel of a reference work to it. Text appears in large blocks, is illustrated sparsely, and has no callout texts or pull quotes. Key words are bolded but get no more embellishment, which again suggests a reference rather than an instructional work. I’m sure this material could be the groundwork for a more reader-friendly presentation, if someone wanted less of a reference and more of a textbook.

This might be the most appealing point of the text for me. As I mentioned earlier, I like the overall sequence that the author follows, but at the same time I can appreciate how the sections can be detached and still stand alone. The logic follows principles and theory through to fundamentals, then diverges to cover the details that fit more complex or esoteric versions of research. There is enough statistical explanation to avoid vague generalizations, but at points I expect it would overwhelm a beginner. I would prefer ethics was near the start of the text, rather than an epilogue; our course is arranged to require students to complete ethics training before they may pursue later assignments. But this is easily solved.

On the whole the text is satisfactory, the layout from page to page is acceptable, but there’s a minimum of graphic elements or visual components. Some of the statistical formulas or graphs are low-quality, or have suffered compression artifacts. Their appearance in the text is logical though, and the few tables or diagrams that do appear are in color, with arrows or labels to ease interpretation. The table of contents is primitive, and there is no way to navigate specific tables or diagrams except moving page by page in sequence. External sites are hyperlinked, and the table of contents has been designed for electronic use, but there are no cross-reference features. This gives the text the feel of a word processed document converted to a PDF format, intended to be printed. Overall, the core content is strong, as a printed book it is probably acceptable, but as an electronic textbook it lacks some contemporary features.

I have found very few grammatical errors or incomplete sentences, and none of those were so flagrant as to make the text unusable. If this had been submitted as an academic work it would likely earn some criticism for style or grammar (the author seems to follow APA style, but tends to footnote references simultaneously), but this never impedes the delivery. The text is readable at a collegiate level without becoming over-academic, or for that matter, casual.

The text manages to broach sensitive issues in a level and balanced format; in particular the ethics section manages to discuss some well-known failings in past research without becoming overly critical of the researcher or the participants. Arguably, research and its underlying processes are mostly mechanical (or at least standardized), meaning it is possible for individual researchers to violate cultural, ethnic, racial, or other boundaries, but the underlying science is generally unconcerned with those issues. In that sense, the book has very few opportunities to broach hot-button topics except when dealing with historical or ethical examples.

I appreciate this text as a starting point for a more accessible design, or as a background reference for a full course introducing social science research. I see it as a foundation text or an external source for students who seek a concise fallback for lessons, and with content that is compatible with other textbooks. In many ways it needs much more to compete with established textbooks or dedicated electronic learning tools, and in some places I would like more references for the material that is included. On the whole though, I would consider this as the core text for my next introductory research course.

Reviewed by Krystin Krause, Assistant Professor, Emory and Henry College on 4/10/19

This text covers the core elements of a social science research methods course at the undergraduate level. While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. The concise chapters are undergraduate-friendly and will make a solid foundation with the addition of supplemental reading assignments that show examples of the concepts discussed in the textbook. There is no glossary or index, but keyword searching in the pdf copy is simple and effective.

The text seems to be an accurate reflection of social science research methods, particularly when considering causal inference and hypothesis testing. If your course is also covering descriptive inference, you would want to supplement the text with additional material.

Research methods is not a subject that changes quickly, and thus this text will not become obsolete quickly. The only things that may need updating over time are any links that lead to pages that no longer exist. Any other updates will be relatively easy and straightforward to implement.

The text is written in a style that is accessible for undergraduates. It follows the conventions of including relevant key words and phrases in bold and includes easy to follow definitions of terms. I anticipate that undergraduates will also appreciate how concise the text is.

The chapters are consistent in both terminology and framework. It offers a unified organization that also allows for mixing and matching chapters if an instructor wishes to teach the chapters out of order.

The organization of the text lends itself to be adapted to any introductory social science research methods course, regardless of what order the instructor wants to place the topics being discussed. Chapters could be taught out of order and can be subdivided accordingly.

While it is certainly possible to break apart to teach the text in a different order than how the chapters are originally offered, the progression of the text from the introduction to the chapters on qualitative data analysis is both logical and clear.

The text is free of interface issues, and charts and images appear to be clear and correct. The only exception to this are the links found in the sample syllabus at the end of the book. I was only able to get one of the links to work.

No grammatical errors jumped out at me. There are a few here and there, but they are not distracting for the reader.

The text is not culturally insensitive or offensive.

Because the book is concise, I would recommend its use in addition to other supplementary resources such as class lectures, academic articles that demonstrate the methods discussed in the textbook, and projects that allow students to experience the methods first-hand. It would make a good alternative to more elaborate basic research methods textbooks when the instructor wishes to keep costs for the students low.

Reviewed by Mari Sakiyama, Assistant Professor, Western Oregon University on 4/5/19

The textbook covers the major key elements that are essential in research methods for social science. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. With the use of additional reading... read more

I did not notice any errors or unbiased content. The author had provided accurate information with simple/straightforward examples that can be understood by students with various discipline in social science.

Given the nature of the subject, the content is considered to be up-to-date. However, although there will not be too many changed expected in the research strategies and designs, it is important to note that some of the sampling procedure have been facing some changes in recent years (e.g., telephone survey, online sampling frame).

The textbook provided the content in a clear and concise manner. The author, instead of providing a complex list of academic jargon/technical terminologies, but rather clarified and explained these terms in a simple and straightforward fashion.

Overall, the content was consistent throughout the textbook. Starting with a broad/general statement of each chapter topic, the author narrowed it down to smaller element which is easy for the reader to follow and understand. As he provided in CH.6, it might be even more helpful to have summaries for each chapter.

This textbook is certainly divided into smaller segments, but maybe too small (short). However, as mentioned above, this problem can be solved by adapting additional readings.

The textbook is significantly reader-friendly and well-structured. Although some instructors prefer to cover some chapters earlier (or later) in their semester/term than others, this is just a personal preference. There are no issues with the author’s organization of the textbook.

Overall, the use of indentations, bolding, italicization, and bullet points, was consistent. However, many of the images were blurry (e.g., Figure 8.2, Table 14.1) and some fonts were smaller than others (i.e., pg. 34).

I did not notice any grammatical errors. Even I had missed some, they would not be destructions for the reader. (Note: The scale is confusing. What I mean by '5' is the least amount of grammatical errors were found)

The author did not use any concept that was insensitive or offended people and/or subjects from various backgrounds. (Note: The scale is confusing. What I mean by '5' is the least amount of cultural insensitivity or offensiveness were found)

See my comments above.

Reviews prior to 2019 are for a previous edition.

Reviewed by Candace Bright, Assistant Professor, East Tennessee State University on 11/7/18

There are some key elements that I would expect to be in a social science research methods book that are missing in this book. I think this comprehensiveness may be appropriate for an undergraduate course (with some supplementation), but the text... read more

The information in the book seems accurate. When necessary, it is cited appropriately.

The content is very relevant. Because the book focuses on methods, it does not need too much change over time. It was published in 2012. The main area that might need to be updated in the discussion regarding the Internet and how it impacts our research options. Perhaps more could be added on machine learning, AI, web-scraping, and social media in general. I increasingly see studies conducted either using social media content or recruiting through social media; neither of these are addressed in this book.

I really like the way the book is laid out. In particular, the qualitative and quantitative analysis sections are well organized. They succinctly cover a lot of information is a way that is very consumable. There were some instances, however, where I thought wording lacked clarity or definitions needed further explanation.

I do not see any issues with consistency.

I like the organization of this book and each chapter does a good job of standing alone on important topics within research methods. The sections within the chapters are clearly marked and logically organized.

The organization is clear and logical. It covers important concepts in research methods in the same order in which they are typically taught, with the exception of ethics. In this book, ethics comes last, whereas I would have taught it earlier.

This might be minor, but I noticed some places where the spacing was different and it was a little distracting. Overall, it is well formatted.

I didn't notice any grammatical errors.

Overall, the text book could use more examples and applied examples, but when present, I find them culturally appropriate.

I have mixed feeling on the image on the cover and the limited visuals within the book. I also don't feel like this textbook has enough visuals or figures that could be used to support comprehension of the materials. More examples would also be helpful. Overall, however, the author has presented a lot of information succinctly and I look forward to using this text (in parts) in future methods courses.

Reviewed by Alysia Roehrig, Associate Professor , Florida State University on 11/5/18

This text provides an overview of many important issues for my graduate research methods course in education. There are a few important topics missing, however. In particular, types of correlational designs and mixed-methods designs would be important to include. Likewise, single-subject designs are not mentioned at all. I will have to supplement these areas with other readings. I also think more about specific threats to internal and external validity should be provided, along with information about when and how certain threats are avoided. There is no glossary but being an online text, it is simple enough to search for certain terms.

Content seems to be error-free and unbiased for the most part. However, I have an issues with the language in chapter 2 about about strong and weak hypotheses because it seems to treat the experimental/causal hypotheses preferentially. The author also states that hypotheses should have IVs and DVs...but what about non-experimental hypotheses?? I think students could be misled by this and I think this requires a lot of unpacking. Thus, I do sense somewhat of a prejudicial treatment of quantitative and experimental research methods. I plan to add information to pages 13 and 15 about how qualitative methods do not involve testing hypotheses though the results might be an inductively derived hypothesis or nascent theory.

The content covered is pretty standard and basic and so not likely to be out-dated soon.

The writing is straightforward and easy to follow.

The use of terms and framework seems to be consistent throughout the book.

The chapter and subject headers all seem to be clear. They will make it easy to select sections for assignment or reordering if revising for use.

The order of topics makes sense and is aligned with the process of conducting research.

The hotlinks in the table of content are nice, but additional navigational aids would be helpful. For example, a back to the Table of Contents (TOC) button would be nice, as well we a list of all subsections (hotlinked) added to a long version of the TOC.

I have not noticed any egregious problems.

There are not many examples, which means there is little opportunity to offend.

Reviewed by Eddie T. C. Lam, Associate Professor/Editor-in-Chief, Cleveland State University on 9/12/18

The book provides ample information for a research course, but it may not meet the needs of every instructor. For this reason, the book should include a few more chapters so that course instructors can have more options for a semester-long research course. For instance, at least one chapter should be on nonparametric statistics and their applications on research studies, while another chapter should be on research paper writing (e.g., what should be included in the Introduction, Methods, Results, Discussion, and so on). For the Appendix, it is nice to provide a sample syllabus for the instructors, but the students may want a sample research paper in proper journal or thesis/dissertation format.

Most of the information presented in this book is accurate. The author has mentioned in Chapter 5 (p. 37) that “construct validity” will be described in the next chapter, but I don’t see any construct validity in Chapter 6 or Chapter 7. In addition, the author may want to emphasize what “alpha is set to 0.05” means. Does it mean the p-value has to be less than 0.05 (p. 125) or p ≤ 0.05 (p. 130) to reject the null hypothesis?

In terms of content, the book has fairly good amount of information. However, it is also obvious that many terms appeared in the last few decades are missing from the book. For example, Survey Monkey and social media can be included in Chapter 9 (Survey Research) and structure equation modeling can be introduced in Chapter 15.

The information is presented in layman’s terms without any jargon. New terms are bolded with clear definition, and sometimes they are illustrated with examples.

The terminology and framework are consistent throughout the text.

The chapters are logically presented and they are grouped under different sections. As mentioned before, the text should add a few more chapters for the course instructors to select from.

In my opinion, “Chapter 16 Research Ethics” should not be standalone (under the “Epilogue”) and it could be part of the “Introduction to Research” (i.e., the first few chapters).

The text does not have any significant interface issues, though the font size of the figures can be larger (e.g., they should not smaller than the font size of the text).

Overall, the text contains very few grammatical errors. However, in a number of occasions, a comma is added for no reason, such as “. . . we must understand that sometimes, these constructs are not real . . .” (p. 44). It is also unnecessary to always add a comma before the word “because.”

The content of the text is not culturally insensitive, and the author does not present any offensive statements or comments anywhere in the text.

It’s time to have a second edition.

Reviewed by Amy Thompson, Associate Professor, University of South Florida on 6/19/18

This text is a nice overview of some of the key points in social science research. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It should be noted that there is more of a focus on... read more

Overall, the text seems accurate. There are some cases when the author gives advice that I don't agree with (i.e. advises against even-numbered Likert scale items, p. 48; encourages people not to do "trendy" research, such as that on new technology, p. 24). Even so, most of the information seems to be accurate.

The book is relevant. It gives a good overview of the theories and methods, which change little over time. I would suggest a few updates, however. Currently, there is controversy on the over-reliance of the p-value, and it would be useful to include some of this discussion on p. 125. Also, on p. 73, the author talks about "mail-in" and "telephone" surveys as a research method, and even goes on to say on p. 74 that most survey research is done by self-administered mail-in surveys with a pre-paid return envelop. This information needs to be updated, as currently, much of the survey research is done via online platforms.

The book is quite clear and provides succinct definitions.

The book seems consistent throughout.

The chapters are short and very readable. There would be no problem dividing the chapters up for a class, or using a portion of the book.

The topics are presented in a logical manner.

The text in some of the tables is blurry, especially when enlarging the PDF. Perhaps the print copy is clearer. The text outside of the tables is clear.

I didn't have any trouble reading or understanding the text.

This book is not offensive.

Overall, this is a good book to have as a reference or an additional text for a class. For my field, it wouldn't be sufficient to use as a stand-alone text. Although its intended audience is graduate students, it's a bit too basic for Ph.D. students, in my opinion. It would be a good text for an intro to research class at the UG or MA level, as a supplemental text. I would recommend it to Ph.D. students to use as a reference because of the key terms included. It's great that a resource like this is available for free to students and faculty in a wide variety of disciplines.

Reviewed by Huili Hao, Assistant Professor, University of North Carolina Wilmington on 5/21/18

This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in social science will find these topics useful in developing their research method skills. However, the book falls short on the depth of the essential concepts. It would also benefit from offering more practical examples for some of the theories or terminology. A glossary is not found within the text, although the table of content lists the topics covered in each of the modules.

Overall, this textbooks seems to be accurate.

The relevancy and longevity of this book are great. It focuses on fundamental research methods as well as incorporates current research approaches. Given the nature of research method that does not change drastically, content is up-to-date and won’t make the text obsolete within a short period of time. The topics are written in the way that necessary updates will be relatively easy and straightforward to implement.

The text is written in a logical and concise fashion. The text is easy to follow. I did not find any jargon or technical terminology used without explanation.

The text consistently matches the topics outlined in the table of content.

The text is clearly organized into five modules: introduction to research, basics of empirical research, data collection, data analysis, and research ethics. It also includes a course syllabus, which is nice and useful. Each of the modules / chapters can also be used as subunits of a research method course without putting the reader at a disadvantage.

The table of content is clear and the chapters are organized in a logic order.

I downloaded the PDF version of the textbook and find it easy to read offline. The formatting, navigation and images/charts seems clear and appropriate.

I had no trouble reading or understanding the textbook.

Overall, this is a good textbook that covers a broad range of topics important in research method. As this textbook is designed as a succinct overview of research design and process, more practical topics are not included in much detail such as how to conduct different statistical analyses using SPSS or SAS, or how to interpret statistical analysis results. It would require additional materials / textbooks for graduate level research method courses.

Reviewed by Jenna Wintemberg, Assistant Teaching Professor, University of Missouri on 5/21/18

I use almost the entire text in an undergraduate Health Science research methods course. I do supplement the text with additional readings on: -selecting a research topic -developing a research question -how to read scholarly articles -how to search the literature -mixed methods research -community-based participatory research -disseminating research findings -evidence-based practice

I have found this text to be accurate, error-free and unbiased.

The content is written in a way that will allow for longevity of use. I compliment this text with current peer-reviewed journal articles which are relevant to my students' career paths and can be updated more regularly.

I have found the book to be clearly written and appropriate for upper-level Health Science undergraduate students. Technical terminology is sufficiently defined.

The text uses a consistent framework throughout.

The text is easily divisible into smaller reading sections. I assign the chapters in an alternative order and students have not had problems with this.

I assign the chapters in an alternative order for my undergraduate students. For example, I have students read chapter 1 following by chapter 16 (research ethics).

There are no interface issues.

The text is free of grammatical errors

The text is not culturally offensive.

Because of the basic nature of the materials presented and clear writing, my upper level undergraduate students have done well with this text. The brevity of the chapters and bolded key terms particularly appeal to the students. I do have to supplement the text with journal articles and other materials. However, I am pleased with this straight-forward text and will continue to use it as the main text in my course moving forward.

Reviewed by Amy Thompson , Associate Professor, University of South Florida on 3/27/18

Reviewed by Debra Mowery, Assistant Professor, University of South Florida on 3/27/18

The text covers all of the areas of basic research information that I cover when I teach research and research methods in the social sciences. The table of contents is straight forward, and the chapters are arranged in a fluid, logical order. The nice thing with this text is that you could rearrange as you see fit for your course without an issue. There is also a sample syllabus in the appendix which could be useful when setting up a course. I feel this text is great for students who may not necessarily be interested in research as a job prospect (their interests may be more clinical in nature) but need the basics of research in a clear, easy to understand, and straight forward format.

I felt the content of this text is accurate, unbiased, and free of any glaring errors..

This text appears to be up-to-date including issues such as web-based or internet surveys and questionnaires. I did see that the copyright for this text was 2012 so not sure if revisions or updates to the original have happened or not. It seems that there should be a way to document if this is the latest version of the text. This may be useful information for users of this text.

This textbook is written in a concise and easy to read and understand manner - it is very user-friendly. This is a plus for students - it means they may actually read the text! Jargon and acronyms were appropriately defined with an explanation of how the terms originated and came to be utilized in research. This is appealing to me as an instructor so there is background information for the students.

The consistency of this text is uniform throughout. One appealing issue I liked was the use of social science examples when explaining topics like theories or paradigms. In some research texts examples are utilized but they may not necessarily be in the discipline that you are teaching.

I do like that this text is divided into 16 chapters which is perfect for a 15/16 week semester. The chapters are not so overwhelming that other supporting readings cannot be assigned to students as well to assist with explanation of the weekly topic. The text serves as a great base for building weekly assignments/readings for students.

The majority of the text is presented in a logical format. One issue I had with the order of the chapters in the text was including Ethics at the end in the Epilogue as if it was an after thought. Ethics, ethical behavior, and rigor are a must in research and should be addressed early on in the research process. Having said this, I feel the chapter on Ethics should be moved up further in the chapter line-up (possibly to chapter 2 or 3).

I did not experience any navigation problems. There was however, distortion with many of the images especially the graphics that were utilized throughout the text. A review of the images/graphics and an update to them would be useful. If this e-text has not been updated since 2012 this may be the issue for the distorted figures.

There are a few grammar/spelling/word choice errors. The errors do not effect the content of the text but when reading it makes you pause and think - what is trying to be said here? It might be useful to the author to have the text proofread or copy edited to resolve these issues.

In reviewing this text I did not see any examples that might be deemed offensive or insensitive to other cultures, orientations, ethnicities, etc,

Reviewed by Kendall Bustad, Clinical Assistant Professor, University of Maryland, College Park on 2/1/18

This book covers all the important topics in social science research and is approachable regardless of discipline and course level (high school, undergraduate, graduate, and even post-graduate). It provides an introduction to philosophy as well as components of research. You'll find yourself returning to the basics, and it gives strong foundations. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections)

The text does not seem to be biased in any way.

The content of the book is up-to-date. The text included relevant descriptions of current software commonly used in research.

If you want to have a compressed body of knowledge of social science research, you may read this one. Beneficial.

The text consistently matches the book outline. Terms were used consistently throughout the text.

Each chapter can stand along as a separate lecture. The headings, subheadings, an bold items are great additions that highlight important topics or definitions.

Most of the text flows in a logical, clear fashion. However, it may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis.

No issues noted.

There are a few grammatical errors.

There does not seem to be any culturally insensitive or offensive text.

Reviewed by Jason Giersch, Assistant Professor, UNC Charlotte on 2/1/18

The biggest challenge faced when writing a book about research methods is the decision about what NOT to include. Instructors and disciplines within the social sciences vary widely in terms of their expectations of students in an introductory methods course, and thus their needs from a textbook also vary. This textbook does an excellent job setting the stage for what we mean by "research" in the social sciences. Students will develop a solid foundation in the goals and rationales behind the methods social scientists employ. Students will also develop a comprehensive vocabulary in social science research methods. However, the book falls short in the development of students' research skills. Learning about methods is important, but not much is gained from that knowledge unless the student also learns how to execute at least some techniques. Furthermore, there is little guidance for the student regarding how to properly write a research paper, something that many instructors will find disappointing. This book is probably comprehensive enough for a 3-credit methods course with test-based assessments in a program where few students pursue graduate work. But if teaching students to actually conduct and write up research is important to the course, there are much better books out there (although at significant cost).

Content is accurate and unbiased.

The relevance and longevity are strong. This book describes some of the most current methods but still focuses on the foundations of research that will be appropriate for the foreseeable future. Updates could be easily made every five years or so to keep up with methodology.

The writing is very easy to follow with helpful examples. Prose is direct and to the point, giving only the essential information so as to allow the learner to develop a grasp of fundamentals. The section on theory, for example, is refreshingly clear for learners. Graphics aid in understanding the material in many parts.

This textbook uses consistent terminology and framework.

The textbook is appropriately structured for a standard 15 week course and even recommends a syllabus. Adapting it to other formats, like a 5 or 10 week summer course, might be tricky. There are ample headings and sub-headings, however, that allow the text to be divided into smaller chunks, which is nice to see given how many students feel overwhelmed by this topic.

Organization and flow is excellent. From an education and instructional standpoint, I wouldn't change the organization.

The simplicity of design is a strength -- students should have no difficulty opening and viewing the text on a wide variety of devices. On the downside, there are no bells and whistles that many some students have come to expect from online textbooks.

The casual writing style makes it very accessible, but one consequence is the very occasional grammar problem. It's a trade-off, I think, that is worth making.

Research methods are pretty "culturally-neutral", so there's nothing in it I would see as insensitive or offensive. That being said, the text recommends SPSS and SAS as software to use while neglecting free options (like R) or more ubiquitous programs (like Excel). For a textbook intended to keep costs at zero, these are glaring omissions.

I could certainly see this book being used as an accessible and low-stress introduction to the world of research methods in the social sciences. The main improvements I would like to see would be (1) sidebars throughout that guide students through the paper-writing process and (2) activities using datasets for students to actually perform some of their own quantitative analyses. Perhaps a companion volume could address these needs.

Reviewed by Nathan Favero, Assistant Professor, American University on 2/1/18

This text provides a fairly comprehensive coverage of topics. It is broad, hitting most of the major topics I need to cover in an intro PhD seminar for social science research methods (I'm teaching public administration/policy, political science, and criminology students). That said, there is not a ton of depth in this textbook. I don't view that as a negative; I prefer having a textbook that gives a basic outline of essential concepts and then fleshing this out with supplemental readings, but some might prefer a textbook that goes into more depth.

Overall, this textbook is accurate but not perfect. Sometimes I wish it was a bit more precise, particularly in coverage of quantitative topics. But I use another textbook to more fully cover quantitative topics anyway for my course.

I would say this textbook reads as modern and relevant, although perhaps it could do more to address emerging methodological concerns in social science disciplines (p-hacking, replication, pre-registration of research designs, etc.).

The textbooks is very accessible and easy to read for someone new to the disciplines of social science.

The book appears to be consistent.

I've assigned students to read the chapters in a different order than they are presented in the text had have not encountered any problems. Chapters are coherently organized into distinct topics.

The organization of the book is logical.

Overall, this book is easy to read and use. Graphs are not always high-resolution, but they are readable.

I have not noticed many grammatical errors.

I have not noticed any clear biases or insensitive handling of material in the book.

I'm delighted to have found this book. It's a great starting point for teaching my students to think about the basics of social science research and provides a nice skeleton on which I can layer more in-depth material for my course.

Reviewed by Holly Gould, Associate Professor, Lynchburg College on 8/15/17

The author states that the text is not designed to go in-depth into the subject matter but rather give a basic understanding of the material. I believe the author covers the necessary topics with enough depth to give the reader a basic... read more

I found no errors in content and no observable bias in any of the chapters.

This text will continue to be relevant because of the nature of the subject matter. Updates may be needed to reflect more current research or trends, but no major changes should be necessary.

The text is written clearly and succinctly. The text is understandable for those who are new to the subject matter.

I found no inconsistencies in the text.

The text is divided into logical chapters, and subheadings seem to be appropriate. Chapters can be read fairly easily in isolation without putting the reader at a disadvantage.

The topics are presented in a logical fashion. Some of the chapters have summaries or conclusions, while other chapters seem to end abruptly. It would be helpful to the reader to have a summary statement at the end of each chapter.

I downloaded and read the text in a PDF reader and had no trouble with formatting, navigation, or images/charts.

The text contains some grammatical errors but the errors are minor and do not distract the reader.

This text is well written and I would recommend it to an individual looking for a bare bones book on basic research methods. It contains information essential to understanding quantitative and qualitative research. The charts and images provided enhance the understanding of the text. At times, the author digs a little deeper into background and formulas for certain statistical ideas, which may be unnecessary to someone looking to understand the basics (e.g. the formula for Cronbach's alpha). Some chapters seem to end abruptly while other chapters have excellent summaries or conclusions. There is one recommendation that goes against the prevailing wisdom on survey design. On page 77, the author indicates that a survey should begin with non-threatening questions such as demographic information. Many experts have written that these types of questions, when asked at the beginning of a questionnaire or survey, can affect the respondents' answers to subsequent questions and should be saved for the end. Aside from these minor issues, this text is a great resource and I recommend it.

Reviewed by Virginia Chu, Assistant Professor, Virginia Commonwealth University on 4/11/17

The text offers an introductory overview to scientific research for PhD and graduate students in social sciences. It covers a broad range of topics, research theories, research process, research design, data collection methods, qualitative and quantitative research, statistical analysis, and research ethics. This book touches on many important topics related to the scientific research process that is typically found in several different text. As the author stated in the preface, this is an introductory book that is minimalist by design, it does not contain in-depth discussions or many examples. This is both a plus and a minus, as it makes the book more compact and allow it to be used by many different disciplines, but may be harder for students to relate. The comprehensive nature of the book allows the reader to be exposed to all the necessary topics, or provides a structure for a course instructor, who then supplements with additional materials to create the depth that is specifically tailored for their discipline. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections), as a new doctoral student will certainly need more details than what is provided in the text to begin their first research endeavor. For example, in the quantitative analysis section, only a handful of basic analysis were discussed in detail (univariate analysis, hypothesis testing, t-test, regression). I would like to see a more practical discussion of ANOVA, as it is a very commonly used statistical analysis tool. These topics may also be more discipline specific, where instructors of research classes can supplement with additional materials. The discussion on research ethics is certainly a nice addition to the book where many other research methods texts lack. An index/glossary is not included with the text, but the table of content clearly outlines the topics discussed for each module.

The book is overall accurate and unbiased. The book covered different social science research methods fairly. I did notice a discrepancy in Figure 5.1, where “single case study” is plotted on the graph as high in external validity, but the rest of the text frequently brought up case studies (especially single case studies) having the difficulty with generalizability which should have low external validity.

The content of the book is up-to-date. The text included relevant descriptions of current softwares commonly used in research. It will also stand against the test of time as research methods do not change drastically. The content can also be updated to reflect new technological updates. One needed update noticed is on page 120, where the authors cautioned that only smaller datasets can be stored in Excel and larger datasets needs a more elaborate database system. While the statement is still relevant, the numbers the author cited appear to be old and Excel has since been updated to handle larger datasets (1,000,000 observations and 16,000 items) than what the author had listed.

The content is written in a very clear and concise manner. It is easy to read and to follow the author’s arguments. I did not notice any jargon or technical term that was used without explanation.

The book has a modular organization, with each chapter designed to be used for a different lecture. Each chapter is a self contained unit that can be used as its own reading. Each chapter also has subsections that are clearly marked with subheadings. Important terms are also highlighted by bolding, making it easy for the reader to identify the important concepts.

The chapters of the book flows logically from one to the next. The current layout of the text groups all the data collection methods together and all the data analysis methods together. It may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis. This could be easily done based on the course instructor preference.

No interface issues noted.

The text is generally free of grammatical and spelling errors, with the exception of 2 minor typos noticed on page 139 (“Rik”, “riska”).

The text and examples provided are not culturally insensitive or offensive.

The text is easy to read and covers a broad and comprehensive range of topics important for research. I particularly enjoyed the discussion on research ethics which is often missing in many research methods texts. I would recommend discussing that topic earlier, together with research design, as many of these ethical issues and IRB requirements come up during research design phase. As the text is a meant to be a concise overview of the research process, the more practical topics are not covered in as much detail and would require supplementary material.

Reviewed by Brock Rozich, Instructor, University of Texas at Arlington on 4/11/17

The textbook covers the majority of what would be expected for a research methods course. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. The glossary for the text is clear and a sample syllabus is provided by the author for individuals wishing to use this text for their course. The text was lacking an index, which would prove helpful for students.

The text is accurate and up-to-date with research methods in the social sciences. A variety of data collection methods and concepts are discussed in an easy to understand manor.

The content is up-to-date with research methods in the social sciences. The text should be able to prove useful for a research methods or as supplementary material for a statistics course for the foreseeable future. While I looked through this text with a focus on using it for a psychology course, I feel that this text would be useful across other fields as well.

The book was clear and built upon concepts in a thorough manner. Technical terms were well defined, though as mentioned previously, an index would be helpful for this text for students to look up key terms if they became lost. The text would be useful for an upper-level undergraduate or introductory graduate level course.

The text is consistent throughout. There were no notable deficiencies in any of the content provided in each chapter.

The course is broken down into logical subsections and chapters. Introductory topics relating to research methods are provided early and are built upon in subsequent chapters. A sample syllabus and course outline are provided for instructors who wish to utilize the text for their class.

The book is constructed in a well-organized fashion, without any issues of chapter structure.

The PDF version of the text worked wonderfully on a laptop, with no issues of navigation or distortion of images. This text was not, however, viewed on a tablet or e-reader, which many students use for classes. Based solely on use of a PDF file on a laptop, the interface was flawless, however, if you are considering using this for a class, I would test it out on an e-reader/tablet first to make sure there are no issues with format/text size, etc.

The book did not appear to have any noticeable grammar or syntactical errors.

There were no notable instances of cultural insensitivity throughout the text. Examples were broad and not specific to an individual race or culture.

This is a wonderful open source option for a main text for a research methods course or as a supplementary option for a statistics course that also focuses on data collection.

Reviewed by Divya Varier, Assistant Professor, Virginia Commonwealth University on 2/8/17

The textbook adequately covers most fundamental concepts related to research methods in the social sciences. Areas that would need attention: a chapter introducing mixed methods research, and a deeper discussion on Research Ethics. More social science based examples on specific research designs, experimental research would be great. The research process could include steps involved in academic research with information on the publishing and peer review process.

Content is accurate for the most part. I would have liked a more nuanced discussion of reliability and validity concepts- introducing the concept of validity as conceptualized by Messick/Kane is needed. In social science, especially education (the field I work in), masters/ doctoral students need to be introduced to the complex nature of establishing reliability and validity. While the content covered is detailed, a more critical introduction of the concepts as being situated in the obtained scores as opposed to the instrument itself would have made the chapter stronger.

Content is for the most part up to date (see above comments for specific areas: reliability, validity, mixed methods); some examples may become outdated very soon (example of political movements in middle eastern countries for example).

The writing is excellent in terms of clarity. I appreciate the use of straight forward language to explain the multitude of concepts!

The text is consistent in its overall approach to research methods as well as consistent in its use of terminology.

Bold font for key terms is appreciated. More insets/boxes within chapters would be a great addition visually. Addition of research studies and discussion questions would be great.

The chapters are well-organized. Only suggestion would be to introduce research ethics early on in the book.

No issues whatsoever in this regard.

No issues with grammar

The text is best suited for universities in western countries although I did not identify any insensitivity that would hinder teaching and learning of research methods using this textbook elsewhere.

Specific chapters in this book will be useful for me, from an instructor's perspective. For example, Chapter 2 - 'thinking like a researcher' is wonderfully written. The chapter on Interpretive Research and Qual. Data Analysis are thorough and clear in presentation of concepts- I definitely would use these chapters in my Research Methods class.

Reviewed by Rachel Lucas-Thompson, Assistant Professor, Colorado State University on 12/5/16

As acknowledged by the author in the preface, this is intended as a survey book that doesn't cover all topics in great detail. The upside is that this is a flexible text that can be used in many disciplines; the down side is that the text is short on examples, which reduces readability. I also prefer a textbook that provides a more detailed discussion of the following issues, but could supplement the textbook with these discussion in class: a) confounding variables, b) writing a research report, and the parts of a research report, c) evaluating the internal and external validity of a study, d) how we handle Likert and Likert-type scales (with better reflection of the rich controversy about this issue), e) historical background that has informed our current ethical guidelines, and f) more detail about manipulated vs. observed independent variables. Also, the 'research process' section doesn't include a step for going through IRB review and approval, so overlooks an important step in social science research. I think more detail is provided about paradigms and theories than is necessary, but those chapters and sections could be left out of course reading assignments quite easily.

In general, I think this textbook would be best suited to a course where the textbook is seen as an overview to supplement course discussions rather than a detailed coverage of research methods principles.

As far as I can tell, the book is accurate. There are some terms that the author uses that are not widely used in my field (developmental psychology, human development & family studies) but the descriptions are clear enough that I think students will be able to understand what is meant (however, it would be great to acknowledge and discuss some of these variations in terminology so the burden isn't entirely on the students who are still learning these concepts).

Research methods and statistics content are unlikely to change rapidly, although with the increasing use of ecological momentary assessments, daily diaries, and internet sampling techniques, it might be useful down the road to include more detail about those techniques.

The book is easy to read and follow, although the lack of examples to clarify concepts sometimes reduces the clarity of ideas (but is in keeping with the philosophy of the book).

I haven't spotted any problems with internal consistency.

It would be very easy to divide this into smaller reading sections and assign at different time points.

In general the organization makes sense; the only exception is having research ethics as an epilogue, when ethical issues need to be considered before a study is completed.

My two suggestions for increasing are a) hyperlinking the table of contents so that it was easier to find exactly what you want in the textbook, and b) providing a more detailed table of contents (with subheadings) so it's easier to determine where in chapters you should reference.

I haven't found any grammatical errors.

The text is neither culturally insensitive nor offensive.

I think this book is very well-suited for intro graduate level courses in research methods, as long as instructors are comfortable with this as an overview supplement rather than a detailed stand alone resource for students.

Reviewed by Robin Bartlett, Professor, University of North Carolina at Greensboro on 12/5/16

Generally the major topics are covered. The table of contents (chapter listing) makes it easy to find content. Occasionally I found what I thought was a topic covered only minimally in a chapter - but then found additional information in a later chapter (e.g., treats to internal validity). Overall I'd say in comparison to most other texts with which I am familiar that most all topics are covered, to some degree, but some topics are covered less than I would expect in a doctoral level textbook.

I found no errors in fact in the textbook. I found it to be written in an accurate and unbiased manner.

Primarily due to the topic covered (research methods), I do not believe the text will become obsolete in a short period of time. I think updates could be easily added, and if the author decided to cover some topics more thoroughly, that could be accomplished relatively easily, too.

The book is written in an easy to read style. It is easy to understand. Technical terminology is explained appropriately. The author puts many words in bold type and then defines or describes the word. Students will like this approach.

I had no issues as I reviewed the book in terms of consistency of terms used. The text is internally consistent.

The chapters of the book are separated by natural divisions. It would be easy to use this book in a course on research methods, in fact, there is a syllabus included at the end of the book that could be used by a faculty member when course creating.

The textbook topics are presented in a logical fashion. The ordering isn't necessarily the same order I have seen in other texts, but the order is reasonable.

I had no major interface problems as I reviewed the book. Some of the diagrams in the book are a little out of focus, but, they are still readable.

I found no grammatical errors in the sections of the book that I read.

I found no cultural insensitivity in the text. I noticed the examples cited were from articles written by authors from different countries.

The book is easy to read and fairly comprehensive in terms of topics covered. Some topics are covered in less detail than in some other books I've had the chance to read / review. I am most accustomed to finding discussion of theories in separate texts and presentation of statistics that might be used to analyze quantitative data in separate texts. There are even a couple of chapters on qualitative methods in this book. So, the book covers a wide variety of topics and introduces them in a clear way. Topics are not covered in as comprehensive way as in many texts.

Reviewed by Kelly Pereira, Assistant Professor, The University of North Carolina at Greensboro on 12/5/16

This text offers a comprehensive overview of social science research methods appropriate for advanced undergraduate and graduate students. The text covers the basic concepts in theory, research design and analysis that one would expect of a text geared toward the social sciences in general. The text could be easily adapted and/or supplemented to fit any discipline-specific needs. While the text covers a broad array of topics, it is a bit superficial and lacks depth in some areas. More examples and case studies, for example, could improve the text's thoroughness. The text also lacks an index, glossary and discussion questions, all of which would have been quite useful for a text of this nature. I do like that it includes a chapter on research ethics and an appendix with a sample syllabus, however.

Based on my review, the text's content is accurate, error-free and unbiased. I liked that it presented both qualitative and quantitative research methods fairly, as this divide is often a source of bias.

The text contains up-to-date approaches to research methods and presents classic theoretical debates. The methods presented should not become obsolete in the near future. Any new trends in research methodology could be easily updated in future versions of this text. I feel the text will be relevant and useful for multiple years.

The text is generally well written. It presents the information in a clear and concise way. I find it provides sufficient contextualization and examples for graduate students with some background already in research methods. Undergraduates will likely require supplemental materials and additional case studies to grasp some of the concepts covered. The illustrations do help guide understanding of concepts presented.

The terminology and research methods frameworks presented in the text are consistent. The use of bolded terms and illustrations throughout the text provide additional consistency.

The division of the text into the following sections: theoretical foundations, concepts in research design, data collection and data analysis, make it easy for instructors to structure a course and assign readings based on these main foundational areas. This format also enables instructors to easily supplement with other materials.

Overall, this is a well-organized text. Bolded words/phrases throughout the text provide some structure to guide reading. The text is divided into 16 chapters, which corresponds seamlessly with a 16-week semester. This enables instructors to cover one chapter per week, if they so desire, or optionally spend more time on chapters relevant to their course and exclude others. As mentioned earlier, the logical division of the text chapters into the areas of theory, research design, data collection and data analysis, lends to a soundly-structured course and facilitates the assignment of readings and other coursework.

I did not experience any issues with the text's interface, navigation or displays of images/illustrations. The text is in PDF format.

I did not notice any grammatical errors that impeded reading of the text.

I did not come across any culturally-insensitive or offensive passages in the text.

Reviewed by Peter Harris, Assistant Professor, Colorado State University on 12/5/16

This is a comprehensive overview of research design and research methods in the social sciences. The book's introductory sections offer a discussion of the philosophy of science, the history of science, and definitions of some key terms and concepts, which will help students to contextualize their own endeavors - and their own discipline(s) - inside a larger framework. It also tackles the more familiar topics of research design - conceptualization, measurement, sampling, and so forth - and several specific approaches to data-collection. Overall, then, the book is to be commended for tackling both the philosophical issues at stake in research design as well as the 'nuts and bolts' (or 'brass tacks') of actually doing research.

One of the book's touted selling-points is its focus on phases of research that precede data collection. That is, the book aims to train students not only in research methods, but also in the critical tasks of theorizing problems, generating research questions, and designing scientific inquiries - what the author refers to as 'thinking like a researcher.' This is certainly a welcome addition to a textbook on research design, and ought to help students to overcome some familiar stumbling blocks that seem to present themselves during graduate programs.

Because of its breadth, however, parts of the book can sometimes seem thin and underdeveloped. In particular, the chapters on data collection (specific research methods) are less detailed and comprehensive than other books manage to provide. It is hard to give a detailed 'how to' guide to either survey research, experiments, case studies, or interpretive methods in just 10 pages. As a result, instructors will almost certainly want to supplement this book with more detailed material, perhaps tailored to their specific discipline.

Even so, this book is an excellent backbone for an undergraduate or graduate class on research methods. It will have to be read in conjunction with discipline-specific guides to conducting research (and, most likely, alongside examples of good and bad research), but this does nothing to detract from the book's own value: it will certainly offer a valuable overview of key concepts, ideas, and problems in research design and data-collection, and will serve students throughout the duration of their studies and not just for one class.

This book is accurate, error-free, and as unbiased as it is possible to be in the social sciences. Of course, it is possible to imagine those who simply hold different views about what social science "is" or should be; some scholars might bristle at the notion that only knowledge produced according to the narrow strictures of the scientific method can be considered "scientific knowledge," for example, while others might balk at interpretivism being given parity of esteem with what they see as more rigorous methodological practices. But for the broad mainstream of the social sciences, there will be little in this book that stands out as unusual, controversial, or one-sided.

On the whole, the content of this book will remain relevant for a long time. After all, the basics of the scientific method and the fundamentals of research design seem unlikely to change in the foreseeable future. New and cutting-edge strategies of data collection and theory-testing do emerge, of course, but these are probably best delivered to students in the form of discipline-specific books or articles that could be assigned to complement this textbook, which deals more with foundations than it does with current debates.

The book is organized well and information is presented in a clear way. The prose is accessible and each chapter proceeds methodically.

This text is certainly consistent, and proceeds according to a methodical and logical structure. Key terms and concepts are introduced early on, and there are no 'surprises' in later chapters.

This book is organized into chapters, each of which could be used as the keystone reading for a given class session, and each chapter is broken down in easy-to-digest sections, making the book as accessible as possible. The fact that there are 16 chapters mean that the book could support 16 separate class sessions - that is, just enough to orient classroom discussion for an entire semester. That said, each module does not comprise sufficient material for a whole week; the chapters will need to be supplemented with extra reading material, especially in graduate seminars. It is unlikely that instructors will want to assign only part of a given chapter. Overall, the text reads well as a whole and in terms of its individual chapters.

The chapters for this book are organized into five sections: the introductory section, a section dealing with the basics of empirical research, sections on data collection and data analysis, and a final section that deals with ethics in research. This is a sensible and logical structure for the book, and nothing seems out of place. Again, the book is an accessible and smooth read; it will pose no challenges to an informed reader, and there will be nothing in the organization of the book that will be distracting or irritating.

As a single PDF, this book is easy to navigate.

I noticed no spelling or grammatical errors in this well-written book.

I can detect no culturally insensitive or offensive remarks in this book.

It is worth mentioning that this text ought to serve students well throughout their undergraduate studies, graduate careers, and beyond. It is a timeless - if necessarily limited - resource, and be returned to again and again.

Reviewed by Tamara Falicov, Associate Professor, University of Kansas on 8/21/16

The book is divided into sixteen chapters, which seemed a bit intimidating at first. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. This makes the book quite comprehensive in that the book could be used for the length of the semester, one chapter per week. This is a useful model and one can add or subtract if needed. For example, the beginning chapter which discusses what science is and uses vocabulary from the hard or natural sciences may not necessarily be relevant in a social science course, but the author is being comprehensive by explaining the origins of science and the creation of the scientific method.The vocabulary in bold is extremely effective throughout the book.

The book is meticulously researched and I did not note any egregious statements or inaccuracies. There was one strange sentence when the author was trying to contrast a liberal to a conservative’s viewpoint on page 18 that made this reader feel a bit uncomfortable in how one ideological viewpoint was portrayed, but I’m not sure it was necessarily bias; perhaps just the writing was a bit heavy handed

The book makes sure of updated case examples, discusses how students utilize the internet for research, etc. The theories outlined here are the classic important debates, and the breadth of knowledge the author imparts is extremely comprehensive and up to date. this book could definitely stand on its own for many years before changes in the field might necessitate updating.

I found the textbook to be a refreshing read. The writing is very accessible and clear, but can be dense at times (though not in a problematic way—it means that with some of the more challenging material, the students will have to dig a little deeper to glean the information. The writing was very crisp, and to the point.

The book is written in a careful, consistent manner. As mentioned earlier, the vocabulary words in bold are consistent signposts, and there are citations (not too many, not too few) that help structure the book and provide a cogent framework. Sometimes there are summaries and bullet points, and other times there aren’t, so this is not exactly consistent, but it doesn’t detract from the overall work.

The chapters are excellent stand alone essays that could be used interchangeably. Some of them, such as the first chapter, is historical and philosophical, but not essential to understanding social science research methods. The second and third chapters are excellent for the researcher who is just starting out to formulate a research question. It helps them to think about the various theories and approaches available to them in terms of the angle, focus and methodology selected. The later chapters explain in greater detail various kinds of methods such as how to measure constructs, and scale reliability. These are higher order concepts which would be useful to graduate students—chapters 1-3 could not only work for graduate students, but also for upper division undergraduates.

The book was structured in a logical progression. There were no problems there. There was some repetition with various terms such as Occum’s razor, but this is because there is some overlap with concepts which I think is fine, given that some chapters may not be used in the course of a semester.

No problems with typeface, the diagrams and graphs are incredibly useful in breaking down more complex research methods.

There were no problems with syntax, grammar, spelling that I came across, except for a minor typo in chapter 9 in the table of contents.

I felt that the author was careful in his selection of case students to try to be inclusive and culturally sensitive. There was that one sentence that raised eyebrows about liberals versus democrats that I mentioned previously, but it wasn’t a major deal.

I found this book to be extremely useful and of high quality. I will to recommend it to a colleague who is teaching research methods next semester in a different department.

Reviewed by Yen-Chu Weng, Lecturer, University of Washington on 8/21/16

Dr. Bhattacherjee’s book, Social Science Research, is a good introductory textbook for upper-level undergraduate students and graduate students to learn about the research process. Whereas most research methods textbooks either focus on “research design” or on “data analysis”, this book covers the whole research process – from theories and conceptual frameworks to research design, data collection, and analysis. This book is structured as four modules and is very adaptable to instructors who want to teach any portions of the book.

Social science is a quite diverse field, including studies of socio-economic data, human behaviors, values, perceptions, and many others. Not only are the topics wide-ranging, but the research methods and the underlying philosophy of science also vary. Therefore, it is extremely difficult to write a textbook that includes everything. Dr. Bhattacherjee’s book is a nice overview of all these different methods commonly used in the social sciences. It aims for breadth, but not depth. Once could use this book as an entry to the field, but would need to seek additional resources for specific methods or analytical skills.

Based on my review of the book, the content is accurate, error-free and unbiased. However, better consistency with terminology often used in other related fields (such as statistics) would lessen students’ confusion with concepts.

Research methods are not time-sensitive topics and are not expected to change much in the near future. The inclusion of some cases or examples showcasing how social science research methods can be applied to current events or topics would help illustrate the relevance of this book (and social science research).

The book is very clear and accessible. It’s written in a way that is easy to understand. Important terminologies are bolded and these are good signposts for key concepts. A glossary summarizing definitions for the key terminologies would help students understand these key concepts. The book includes some helpful figures illustrating concepts in research design and statistics.

Overall, the book is very consistent.

The author, Dr. Bhattacherjee, structured the book following the research process – from theories, to research design, data collection, and analysis. Each module can be a standalone unit and is very adaptable to instructors who want to teach with either the whole book or individual modules. Although each module is mostly self-contained, it is impossible not to refer to other chapters since research is an iterative process. However, I do not expect this to be a huge problem for someone who wants to teach only a section of the book.

The fact that this book is structured as modules also makes it expandable. For those who want to teach only the philosophy of science or only the research design portion, they can add more details and in-depth discussion to these topics.

The book is well-organized and flows well with the research process. The chapters are clearly titled as well as the subheadings. Some numbering with the subheadings would help with navigation. In addition, a chapter summary/conclusion would also help with summarizing the main concepts of a chapter (some chapters do have a summary, but not all chapters).

The flow of the first module (Introduction to Research) is sometimes confusing – the book jumps between big ideas (scientific reasoning, conceptual framework) and specific details (variables, units of analysis) several times in the first four chapters. I thought that reorganizing the chapters as Ch1, Ch4, Ch3, Ch2 would flow better (from big ideas to specific details).

Since the book is organized by the research process, not by the type of research (qualitative vs. quantitative), Module 3 (Data Collection) and Module 4 (Data Analysis) cover both types of research. As a result, the flow/connection between each chapter are less clear. By reorganizing these two modules into “qualitative research methods and data analysis” and “quantitative research methods and data analysis”, not only would improve the flow of the book, but also better serve researchers who are interested in a particular type of research.

There are no major problems with the book’s interface. Each chapter is clearly titled. I would like to see the subheadings being numbered as well. If the PDF could have the Table of Contents on the sidebar, it would improve the navigation even more.

There are no grammatical errors noticed.

There are no culturally insensitive or offensive materials noticed. The few examples used in the book are very general and not controversial.

This book is a nice walk-through guide for researchers new to the field of social science research. One thing I would recommend adding is examples and cases. With more examples and cases, students would be able to put research methods into context and practice how they can apply the methods to their own research projects.

Reviewed by Dana Whippo, Assistant Professor of Political Science and Economics, Dickinson State University on 1/7/16

For its purpose, as introduced by the author, this is appropriately comprehensive. However, it is much more brief, more concise, than traditional research methods texts for undergraduates – which the text does not claim to be. It lays a sufficient foundation, with room and expectation for the professor to supplement with additional materials. Supplementing would be important if using this in an undergraduate classroom. I appreciate that the author emphasizes the process of research, and takes the time to address, in the first four chapters, the logic and process of research in a way that allows the text to be used in multiple disciplines. Indeed, this is one of the strengths of the book: that it can be used broadly within the social sciences. The text does not provide either an index or a glossary. This is more challenging when planning for its use in an undergraduate research methods class; however, I think that the strengths of this book outweigh the weaknesses.

I have not noticed any errors or bias. The only issue I’ve noticed, as indicated in other parts of the review, is depth. Doctoral students would bring in a sufficient foundation for reading this on their own; undergraduates will need scaffolding and additional resources to competently understand the complexity inherent in research.

The content does not read in a way that seems (either now or in the future) likely to read as dated or obsolete. The discussion of survey methodology and analysis programs will change with technology, but that should be easy to update. One of the book’s strengths is its focus on the foundation of research methods: the relationship between theory and observation, the understanding of science, and the logic that underlies the process of research.

The book is well-written and concise. Bearing in mind the author’s stated target audience of graduate and doctoral students, it is entirely reasonable that this would require additional work and instructor support (extra time and explanations for definitions and examples, for instance) when used in an undergraduate classroom.

The terminology is consistent throughout.

Faculty would be able to easily divide the text into smaller sections, which would be useful as those smaller reading sections could be combined with targeted supplementary materials.

The topics generally flow well as presented; the only exception is having the section on research ethics at the end. However, this chapter would be easy to assign earlier in the semester.

I did not have any problems with respect to interface issues.

I did not notice any grammatical errors that interfered with the reading process.

I did not notice any offensive comments or examples. The book is brief by design; it does not include the numerous examples that populate the traditional undergraduate research methods text. I did not find it offensive or insensitive.

Reviewed by Andrew Knight, Assistant Professor of Music Therapy, Colorado State University on 1/7/16

I have not seen a more comprehensive text for this topic area, and yet it retains a concision that I would have appreciated as a PhD student when I took courses in research methods. I think that the text may lend itself to several different types of courses. The early chapters can by used for more theoretical research courses, especially for new researchers and fundamentals of research courses. The later chapters can be used for "nuts and bolts" courses for addressing specific methodological issues. The appendices are an especially nice touch and added value for faculty to understand how the author uses this text and creates a syllabus to complement it.

There are very few typographical errors, and overall, the text is rigorously unbiased in its scientific method claims and explanations.

The overwhelming majority of the content in this text is classical understandings of research and methodologies that are essential to all graduate students, particularly in business and the social sciences. There is no indication that any of the content will suffer from claims that it is obsolete or irrelevant.

The clarity of the text is sound partly due to the concision of the book. Shorter chapters, easily navigable paragraphs, and other compositional devices make the text accessible to most levels of graduate students. The bolded words invite the reader to create a self-guided glossary, not any different than a textbook in an 8th grade student collection, which is helpful to counter the sometimes sophisticated nature of research theory.

No consistency issues noted.

The chapters have a nice flow to them, and can be "chunked" out for use in more beginner or more advanced courses. One preference of this reviewer would be to assign the ethics in research chapter earlier in the course calendar, and thus earlier in the textbook, so it is part of the foundational aspects of understanding social science inquiry. Meanwhile, the qualitative and two separate quantitative chapters play well together for students who will want to review them before exams or after the course is finished while they pursue a thesis/dissertation.

Again, I think the ethics chapter should be earlier, but that is simply a personal choice and can be altered by my syllabus. One issue that I wonder if graduate students might prefer is if they are not already 13 chapters into a text/course and only then are they getting to a basic concept such as measures of central tendency. Offering some of the nuts and bolts of research methods earlier in the text and tying them into the more theoretical concepts might help with clarity of flow for the typical graduate student.

No issues, nice charts and graphics throughout.

Very few noted.

This text is not insensitive in any way. As a matter of fact, pointing out historical issues in research ethics using some sensitive vignettes actually heightens the importance of research in everyday life.

I'm looking forward to adopting it for courses and using it for my own reflections on research!

Reviewed by Allison White, Assistant Professor, Colorado State University on 1/7/16

This text covers a wide array of topics relevant to social science research, including some that are not traditionally included but are welcome additions, such as a chapter dedicated to research ethics. A sample syllabus for a graduate course on research design is also offered at the end of the book, facilitating course development. The book is comprehensive in its treatment of the central components of research design and the different methodological strategies that researchers can leverage to investigate various research questions. Notably absent, however, is an index, glossary of terms, or questions for discussion, which are frequently included in textbooks devoted to research design.

The content is accurate and unbiased, which may be particularly important for texts on research design, as many fields within social science are intractably polarized between quantitative and qualitative approaches. The book goes a long way toward bridging that gap by treating the multitude of methodological orientations fairly and without obvious preference for one or another.

This book will stand the test of time due to its comprehensiveness and fair and balanced approach to research design. Both cutting-edge and classic approaches to research are discussed and the book may be easily updated as warranted by important developments in the social sciences.

The text is written clearly and accessibly, providing adequate context for most of the jargon and technical terminology that is covered. For this reason, it seems suitable for a variety of graduate-level courses, including research design survey courses and more advanced courses focusing on specific approaches.

The text is internally consistent in terms of terminology and framework.

The book neatly compartmentalizes the topics, making it easily divisible into smaller reading sections that can be assigned at different points within the course. The individual chapters stand on their own and do not require contextualization. Numerous sub-headings throughout each chapter flag the central themes.

The topics in the text are presented in a logical, clear fashion. The topics build productively throughout the textbook, beginning with the basic concepts of research design and culminating with different strategies to approach research.

The book's interface is seamless. Charts and images appear appropriately sized and undistorted and the text is free from navigation problems.

The text does not contain conspicuous grammatical errors.

The text and examples provided in it are not culturally insensitive or offensive in any way. Examples are drawn from universal theories rather than research that is culturally-specific.

Reviewed by Jim Hutchinson, Lecturer, University of Minnesota on 6/10/15

This text covers all the basic concepts expected in a book on social science research. However, it does so at a fairly superficial level. The author says this was intentional in order to provide coverage of essential topics and not distract students. As such, the book seems to do a good job introducing all the essential concepts for graduate research, but supplemental materials are likely needed depending on instructor or student needs.

The book seems to free of errors and bias.

Social science research isn't likely to change greatly so this text should remain relevant for some time and can easily be updated to accommodate new techniques as they arise.

The book is generally well-written and accessible. The writing is clear and there are sufficient examples to help students grasp concepts.

The text appears consistent with others in the field.

The text may be best used as an overview of the research process in social sciences rather than a reference. However, various chapters could also be used alone or as supplement to other materials and excluding chapters not relevant to a particular course should not cause any issues. The author even mentions excluding certain chapters that are actually full courses where he teaches.

The organization and sequence seems very logical.

I accessed the PDF version and did not experience any issues with text or graphics.

I think a good proofread would help. There are a number of places where extraneous words were left in (perhaps when rewriting and changing the structure of a sentence) or where words are not quite right. For example:

"...a researcher looking at the world through a “rational lens” will look for rational explanations of the problem such as inadequate technology or poor fit between technology and the task context where it is being utilized, while another research[er] looking at the same problem through a “social lens” may seek out social deficiencies..."

Such errors are not really problematic but they are a bit distracting at times.

I did not find the book to be insensitive or offensive. Examples used are fairly benign. For example, when discussing the tendency of lay people to view a scientific theory as mere speculation the author uses an example of teacher practice instead of a more charged example such as evolution.

Overall, this is a good book to introduce graduate (and even undergraduate) students to social science research. It is not comprehensive enough to be the only text students encounter, but it would be sufficient for say master's level programs that focus more on capstone or practical "informed by research" projects. Students planning to conduct original research, analyze data and interpret results will likely find this insufficient.

Reviewed by Paul Goren, Professor, University of Minnesota on 7/15/14

This text introduces social science doctoral students to the research process. It can be used in sociology, political science, education public health, and related disciplines. The book does an excellent job covering topics that are too often neglected in research methods classes. Standard texts devote most of their attention to different modes of data collection (e.g, lab experiments, field experiments, quasi-experiments, survey research, aggregate data collection, interpretive and case study methods, etc.). This book covers these materials but also devotes a lot of time to steps in the research process that precede data collection. These steps include formulating a research question, concept definition, theory elaboration, measurement (including reliability and validity) and sampling. There is also cursory coverage of descriptive statistics and inferential statistics (a chapter on each) as well as chapter on research ethics. In terms of coverage, then, the text can be described as comprehensive in terms of topics. In terms of depth of coverage of the topics, the text takes a minimalist approach. That is, the fundamentals of each topic are covered, but there is little discussion beyond the basics. Teachers looking for the perfect text that nails all the key points should look elsewhere or make heavy use of supplements. For instance, in the discussion on concepts, constructs, and variables, the text does not distinguish between latent variables, which are unobservable, and manifest variables, which are observable, as is common in the structural equation modeling tradition used in sociology and psychology. This is a minor omission and there are others one might quibble with. The bottom line is that most key topics in the research process are covered, but the coverage is not terribly deep.

From what I can tell, the book is accurate in terms of what it covers. There are some things that should probably be included in subsequent revisions.

The social science research process is unlikely to change in any signfiicant way for some time; therefore, I suspect the book will be relevant for years to come. The key will be ensuring that the latest research trends/improvements/refinements are added to the book. For instance, internet sampling techniques have come a long way over the past decade and there are now pollng firms that can admister online surveys to representative samples of the broader U.S. population. So long as the author keeps on these develops, this will serve as a useful introductory text for the foreseable future.

This text is extremely and unusually well-written and clear. This is one of the text's greatest selling points. No complaints on this score.

The book is very consistent from what I can see.

This book can work in a number of ways. A teacher can sample the germane chapters and incorporate them without difficulty in any research methods class.

The organization is fine. The book presents all the topics in an appropriate sequence.

The interface is fine. I didn't experience any problems.

I didn't see any errors, it looks fine.

The book is not culturally offensive.

Teachers looking for a text that they can use to introduce students to the research process and cover the foundational components of the research process should find this manuscript sufficient for their needs. Simple additions on slides or class room commentary can easily take care of the various omissions that pepper the text. Indeed, one could use this text in conjunction with discipline specific supplements quite effectively. For instance, in chapter 3 on the research process, the author devotes 5 paragraphs to common mistakes in the research process, such as pursuing trivial research questions or blind data mining. I can see how psychologists, sociologists and political scientists could provide discipline-specific examples to tailor this to their students particular needs. More generally, I suspect that the text could be used in conjunction with germane discipline specific materials quite effectively in research methodology classes. The book is not perfect. I wish there was more discussion on field experiments in the experiment chapter. Other than a brief mention that these are relatively rare, there was nothing. These are indeed relatively rare but that seems to be changing in some fields (e.g. economic, political science), and I think more discussion of this technique is warranted. The chapter on case study methods would benefit from discussion on the historical and comparative methods that are used in various social science disciplines, as well as some discussion on case selection methods. The statistical coverage is very thin and should not serve as the primary source material in any class that covers statistics. For instance, the discussion on the empirical assessment of reliability (for items or scales) does not discuss in depth the assumptions that underlie the various methods nor the modifications that need to be made across different levels of measurement. To take another example, the author presents the formulae for the variance and standard deviation on p. 122 with the customary n-1 in the denominator. Students often ask me why we divide the mean squared deviation by n-1 instead of n, which is what we do for the mean. Professors will need to make sure that their slides include discussion of the degrees of freedom idea and perhaps some discussion on unbiasedness as well. In the inferential statistics chapter there's no discussion on desirable properties of estimators (unbiasedness and efficiency). This is an unfortunate oversight. These could be added very easily using simple graphs. One thing that's lacking is a chapter on statistical graphics. The book makes great use of graphics and other visual aids throughout the chapters, but I wish there as a standalone chapter that introduces simple plots for univariate and bivariate data. This can be supplemented easily enough, but the omission seems odd. Again, this book can serve as an compact introduction in a graduate research methodology class for students across the social sciences, but it would work best in conjunction with deeper and more discipline specific materials prepared by the professor.

Reviewed by Anika Leithner, Associate Professor, California Polytechnic State University on 7/15/14

This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. What I liked in particular is that the author includes information on the ENTIRE research process, including critical thinking and research ethics, in addition to the "nuts and bolts" of research such as operationalization, data collection, and data analysis. I also find it useful that the author includes sections on both qualitative and quantitative research, which is great for an introductory level course. In general, readers can expect to find information on theory- and hypothesis building, operationalization/measurements, sampling, research design, various data collection strategies (e.g. surveys, experiments, etc.), as well as data analysis. The primary reason I did not give this text 5 stars is that the author does not provide a great amount of detail for a lot of the book's sections. He explains in the preface that he purposefully chose to reduce the text to the basics in order to keep the text compact and clutter-free. In general, I tend to agree with this approach, as so many methodology textbooks seem to get lost in examples and case studies without clearly illustrating the research process as a whole. However, as I was reading through this book, I kept thinking that I would need to supplement multiple areas of this book with more information in order to make it truly accessible to my students. To be fair, I think that A) anyone who has taught methods before would be able to use the "bones" of this book to prepare students sufficiently well for class and then easily fill in the blanks, and B) it appears that this text was written primarily with graduate students in mind, whereas I most teach undergraduates. In all, I still think that this is a great free alternative to many textbooks out there, but if your teaching style depends on your text including a lot of explanation and examples (or even applications), then this is likely not the text for you. Finally, this book does NOT include an index or a glossary. Personally, I did not find this to be a problem, as the outline/table of contents is very useful, but perhaps students using the text could benefit from an index that would allow them to quickly look up what they need to know.

I did not detect any errors or any purposeful bias in this textbook! Some readers might find that the author's choice of terminology does not necessarily match what I would consider standard practices in the broader social sciences (e.g. the use of the term "mediating variables" instead of "intervening variables"), but it is always clear what the book is referring to and it shouldn't be too difficult to bridge this "terminology gap." Occasionally, I was a bit puzzled by a definition or an explanation. For instance, the author states that "control variables" are not pertinent to explaining the dependent variable, but need to be taken into consideration because they may have "some impact" on it. I'm assuming the author means that they are not pertinent to the hypothesis being tested (as opposed to them not being pertinent to the explanation of the dependent variable). This type of ambiguity does not occur very often in the textbook and it does not necessarily represent an error. It merely seems to be an issue of miscommunication. Overall, I very much liked this text for its accuracy.

Luckily, research methods do not change drastically in a short period of time, so I expect the longevity of this book to be very high. In my experience, the biggest factor that can make a research text outdated is the use of up-to-date examples and case studies. This text includes very few of either, so I think this text could be used for many years to come.

The book is very clear and accessible, probably largely due to its minimalist approach. Aside from the above-mentioned deviations from broader social sciences terminology on a few occasions, I did not encounter any problems with the jargon/technical terminology used. The only minor problem I noted (which made me I've a ranking of 4 as opposed to 5) was a certain amount of repetitiveness in the earlier chapters, specifically with regard to positivism/post-positivism and the discussion of theory/hypothesis creation and testing.

The book is very consistent. It has a clear outline that matches the natural research process and the author very consistently adhere to this outline. Chapters naturally flow from one another and are logical.

This book is very well organized and easily accessible due to its division into logical chapters and sub-sections. In addition, the author highlights important concepts in bold, making it even easier to follow along. I would have no problem assigning smaller reading sections throughout the quarter/semester.

As mentioned above, the text is very well organized and flows naturally/logically. It follows the research process from critical thinking, conceptualization, to operationalization/measurements, research design, data collection, and data analysis. Research ethics are discussed in an appendix/addendum.

There are no major problems with the book's interface. Occasionally, graphs and tables are not as crisp and visually appealing as they might be in an expensive textbook, but personally, the ability to assign an open source text to my students far outweighs any concerns I might have about the visual attractiveness of a book. This text is easy to read and quite user-friendly.

I detected no grammatical errors.

The text includes very few examples and it is hard to imagine how research methods in general could be offensive to anyone (unless it is the practice of science itself that offends them), but for completeness' sake, allow me to state that I found no instances of insensitivity or offense in this textbook.

This text covers all the basics of the research process. It does not contain a lot of the "bells and whistles" that the expensive traditional textbooks have (e.g. lots of examples, fancy graphs, text boxes with case studies and applications, etc.), but it certainly gets the job done. Personally, I appreciate the compact nature of this text and I would much rather fill in a few gaps on my end, if it means that I can assign my students an open textbook.

Reviewed by Brendan Watson, Assistant Professor, University of Minnesota on 7/15/14

See overall comments. read more

See overall comments.

Dr. Bhattacherjee's "Social Science Research: Principles, Methods, and Practices," is a comprehensive, but a bare-boned (and generic) introduction to social science research. In this case "generic" is actually a positive attribute: because the text covers social science research broadly, rather than sociology, psychology, etc. specifically, this text can easily be adapted to the needs of basic research methods courses in allied disciplines. (I teach an introductory quantitative research course for master's and Ph.D. students in a School of Journalism & Mass Communication). I describe the text as comprehensive, because if my students got a basic grasp of all of the concepts in the book, they'd be well positioned to continue on to more advanced research courses (though the text is less valuable as a reference than more comprehensive introductory texts). But while Dr. Bhattacherjee's introduction says that the book is bare-boned by design -- "I decided to focus only on essential concepts, and not fill pages with clutter that can divert the students' attention to less relevant or tangential issues" -- some topics deserve more attention. For example, Institutional Review Boards (IRB) receive only two short paragraphs, and there is no mention of the history of why such boards were deemed necessary and play an important role in the research process. I'd consider such knowledge essential for students, and this is the type of information I would like a text to focus on so that I can spend class time reviewing more complicated concepts students might have trouble grasping on their own. (Generally I found the writing to be approachable, and concepts to be well explained, though extensive examples are also part of the "clutter" omitted from this book). Another topic I would have liked to see developed further - and perhaps is especially important to the more digitally-savvy crowd interested in the open textbook movement - is the expanding role of the Internet and digital technologies in the research process itself, particularly in the era of "big data." The text, for example, mentions Internet surveys, but there is no conversation about tools one can use to build an Internet survey; how Internet surveys differ from traditional modes of surveying; or the practice of weighting Internet survey results to make them "representative" of the larger population. That said, I am balancing using this text versus a more comprehensive, but much more expensive, commercially produced text. Another thing that this book is missing are instructional resources that commercial publishers provide, but ultimately by using this text I can contribute to creating greater value for my students. However, it would have to be supplemented heavily with other materials, as well as lectures, which is not without a trade-off cost. It's certainly doable, but ultimately means a greater investment of my time, and I have to weigh investing my time in creating hands-on learning opportunities and providing students with thorough feedback on their work with the time I'd have to invest in using a text that is complete, but needs to be much more heavily supplemented with additional materials. Ideally, several faculty with similar teaching needs would team up to combine and adapt several open texts to their courses' needs. Adapting and supplementing this text for my purposes by myself, however, remains a steep, if not insurmountable task for a tenure-track professor. This text, however, is thorough enough to maintain my interested in trying to find a way to make it work.

About the book.

Part I. Main Body

Science and scientific research
Thinking like a researcher
The research process
Theories in scientific research
Research design
Measurement of constructs
Scale reliability and validity
Survey research
Experimental research
Case research
Interpretive research
Qualitative analysis
Quantitative analysis: Descriptive statistics
Quantitative analysis: Inferential statistics
Research ethics

Ancillary Material

This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently being used as a research text at universities in 216 countries, across six continents and has been translated into seven different languages. To receive updates on this book, including the translated versions, please follow the author on Facebook or Twitter @Anol_B.

About the Contributors

Anol Bhattacherjee is a professor of information systems and Citigroup/Hidden River Fellow at the University of South Florida, USA. He is one of the top ten information systems researchers in the world, ranked eighth based on research published in the top two journals in the discipline, MIS Quarterly and Information Systems Research , over the last decade (2001-2010). In a research career spanning 15 years, Dr. Bhattacherjee has published over 50 refereed journal papers and two books that have received over 4,000 citations on Google Scholar. He also served on the editorial board of MIS Quarterly for four years and is frequently invited to present his research or build new research programs at universities all over the world. More information about Dr. Bhattacherjee can be obtained from his webpage at http://ab2020.weebly.com .

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Research paper

Writing a Research Paper Introduction | Step-by-Step Guide

Published on September 24, 2022 by Jack Caulfield . Revised on March 27, 2023.

The introduction to a research paper is where you set up your topic and approach for the reader. It has several key goals:

Present your topic and get the reader interested
Provide background or summarize existing research
Position your own approach
Detail your specific research problem and problem statement
Give an overview of the paper’s structure

The introduction looks slightly different depending on whether your paper presents the results of original empirical research or constructs an argument by engaging with a variety of sources.

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Step 1: introduce your topic, step 2: describe the background, step 3: establish your research problem, step 4: specify your objective(s), step 5: map out your paper, research paper introduction examples, frequently asked questions about the research paper introduction.

The first job of the introduction is to tell the reader what your topic is and why it’s interesting or important. This is generally accomplished with a strong opening hook.

The hook is a striking opening sentence that clearly conveys the relevance of your topic. Think of an interesting fact or statistic, a strong statement, a question, or a brief anecdote that will get the reader wondering about your topic.

For example, the following could be an effective hook for an argumentative paper about the environmental impact of cattle farming:

A more empirical paper investigating the relationship of Instagram use with body image issues in adolescent girls might use the following hook:

Don’t feel that your hook necessarily has to be deeply impressive or creative. Clarity and relevance are still more important than catchiness. The key thing is to guide the reader into your topic and situate your ideas.

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This part of the introduction differs depending on what approach your paper is taking.

In a more argumentative paper, you’ll explore some general background here. In a more empirical paper, this is the place to review previous research and establish how yours fits in.

Argumentative paper: Background information

After you’ve caught your reader’s attention, specify a bit more, providing context and narrowing down your topic.

Provide only the most relevant background information. The introduction isn’t the place to get too in-depth; if more background is essential to your paper, it can appear in the body .

Empirical paper: Describing previous research

For a paper describing original research, you’ll instead provide an overview of the most relevant research that has already been conducted. This is a sort of miniature literature review —a sketch of the current state of research into your topic, boiled down to a few sentences.

This should be informed by genuine engagement with the literature. Your search can be less extensive than in a full literature review, but a clear sense of the relevant research is crucial to inform your own work.

Begin by establishing the kinds of research that have been done, and end with limitations or gaps in the research that you intend to respond to.

The next step is to clarify how your own research fits in and what problem it addresses.

Argumentative paper: Emphasize importance

In an argumentative research paper, you can simply state the problem you intend to discuss, and what is original or important about your argument.

Empirical paper: Relate to the literature

In an empirical research paper, try to lead into the problem on the basis of your discussion of the literature. Think in terms of these questions:

What research gap is your work intended to fill?
What limitations in previous work does it address?
What contribution to knowledge does it make?

You can make the connection between your problem and the existing research using phrases like the following.


Although has been studied in detail, insufficient attention has been paid to .	You will address a previously overlooked aspect of your topic.
The implications of study deserve to be explored further.	You will build on something suggested by a previous study, exploring it in greater depth.
It is generally assumed that . However, this paper suggests that …	You will depart from the consensus on your topic, establishing a new position.

Now you’ll get into the specifics of what you intend to find out or express in your research paper.

The way you frame your research objectives varies. An argumentative paper presents a thesis statement, while an empirical paper generally poses a research question (sometimes with a hypothesis as to the answer).

Argumentative paper: Thesis statement

The thesis statement expresses the position that the rest of the paper will present evidence and arguments for. It can be presented in one or two sentences, and should state your position clearly and directly, without providing specific arguments for it at this point.

Empirical paper: Research question and hypothesis

The research question is the question you want to answer in an empirical research paper.

Present your research question clearly and directly, with a minimum of discussion at this point. The rest of the paper will be taken up with discussing and investigating this question; here you just need to express it.

A research question can be framed either directly or indirectly.

This study set out to answer the following question: What effects does daily use of Instagram have on the prevalence of body image issues among adolescent girls?
We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls.

If your research involved testing hypotheses , these should be stated along with your research question. They are usually presented in the past tense, since the hypothesis will already have been tested by the time you are writing up your paper.

For example, the following hypothesis might respond to the research question above:

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The final part of the introduction is often dedicated to a brief overview of the rest of the paper.

In a paper structured using the standard scientific “introduction, methods, results, discussion” format, this isn’t always necessary. But if your paper is structured in a less predictable way, it’s important to describe the shape of it for the reader.

If included, the overview should be concise, direct, and written in the present tense.

This paper will first discuss several examples of survey-based research into adolescent social media use, then will go on to …
This paper first discusses several examples of survey-based research into adolescent social media use, then goes on to …

Full examples of research paper introductions are shown in the tabs below: one for an argumentative paper, the other for an empirical paper.

Argumentative paper
Empirical paper

Are cows responsible for climate change? A recent study (RIVM, 2019) shows that cattle farmers account for two thirds of agricultural nitrogen emissions in the Netherlands. These emissions result from nitrogen in manure, which can degrade into ammonia and enter the atmosphere. The study’s calculations show that agriculture is the main source of nitrogen pollution, accounting for 46% of the country’s total emissions. By comparison, road traffic and households are responsible for 6.1% each, the industrial sector for 1%. While efforts are being made to mitigate these emissions, policymakers are reluctant to reckon with the scale of the problem. The approach presented here is a radical one, but commensurate with the issue. This paper argues that the Dutch government must stimulate and subsidize livestock farmers, especially cattle farmers, to transition to sustainable vegetable farming. It first establishes the inadequacy of current mitigation measures, then discusses the various advantages of the results proposed, and finally addresses potential objections to the plan on economic grounds.

The rise of social media has been accompanied by a sharp increase in the prevalence of body image issues among women and girls. This correlation has received significant academic attention: Various empirical studies have been conducted into Facebook usage among adolescent girls (Tiggermann & Slater, 2013; Meier & Gray, 2014). These studies have consistently found that the visual and interactive aspects of the platform have the greatest influence on body image issues. Despite this, highly visual social media (HVSM) such as Instagram have yet to be robustly researched. This paper sets out to address this research gap. We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls. It was hypothesized that daily Instagram use would be associated with an increase in body image concerns and a decrease in self-esteem ratings.

The introduction of a research paper includes several key elements:

A hook to catch the reader’s interest
Relevant background on the topic
Details of your research problem

and your problem statement

A thesis statement or research question
Sometimes an overview of the paper

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

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Introduction to Research Methods: A Hands-On Approach

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The SAGE edge site for Introduction to Research Methods by Bora Pajo offers a robust online environment you can access anytime, anywhere, and features an impressive array of free tools and resources to keep you on the cutting edge of your learning experience.

Introduction to Research Methods: A Hands-On Approach makes learning research methods easy for students by giving them activities they can experience and do on their own. With clear, simple, and even humorous prose, this text offers students a straightforward introduction to an exciting new world of social and behavioral science research. Rather than making research methods seem intimidating, author Bora Pajo shows students how social science and behavioral research can be an easy, ongoing conversation on topics that matter in their lives. Each chapter includes real research examples that illustrate specific topics that the chapter covers, guides that help students explore actual research challenges in more depth, and ethical considerations relating to specific chapter topics.

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We gratefully acknowledge Bora Pajo for writing an excellent text. Special thanks are also due to Douglas Cooper, Brenda Gill, and Shalini Tendulkar for developing the ancillaries on this site.

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IN COLLECTIONS

Uploaded by station31.cebu on July 1, 2022

Introduction to Research Methods

Eric van Holm, PhD

1 Introduction to the Book

“The true path to wisdom can be identified … it has to have practical application in your life. Otherwise, wisdom becomes a useless thing and deteriorates, like a sword that is never used.” - Paulo Coelho, “The Pilgrimage”

This book is intended as a practical introduction to research methods in the social sciences. If you pursue research academically or professionally, it will probably not be the last book you need to read on the subject. This is intended as something of a gentle introduction with a focus on the applications of the information and examples.

There are a lot of terms that many such textbooks would include that are left out of this edition. I believe that learning is like pouring water into a cup. Once the cup is full, you can keep pouring but the cup wont hold more water. What you should do is drink the water before you refill it. The analogy gets a little bit stretched there, but “drinking the water” stands in for using the information. Once you actually understand the basics in this text, you’ll be ready to read a more advanced book that fills you back up.

So how did I decide what to leave out and what to include? I gave preference to the terms and information I need in my working life as someone who does research. Terms like inductive and deductive research are left out, not because they are unimportant, but because I rarely encounter them. Their definitions might be good material for a test on the terms in this book, but I don’t believe they are fundamentally important to your ability to engage with published research or conduct basic research yourself.

Research is best learned through practice. Like many classes, it is hard to really understand the difference between the different terms and ideas unless you’re actually using them for yourself. This book is written with the understanding that the subject is hard to internalize, and so real world examples are offered where they can be. But that’s not enough to make you an expert. And in fact, it’s hard for anyone to be an expert - there are always new methods and techniques to learn that can improve the ability of researchers to answer important questions. But this book is a good place to start, or at least I hope it is.

With that, I have to give a warning. If you take research methods from another teacher in the future, things might be described differently. That means I’ve sometimes ignored esoteric terms that you wont encounter outside a research methods class. And sometimes I define the terms I use slightly differently than others would. The goal is for this book to be approachable for students who have no background in the subject, aren’t interested in methods, and don’t like statistics.

My primary goal is to impart some of my excitement for research and statistics to you. If I fail in that, I hope I can at least make you better able to engage with the copious amounts of research that will shape policy and your behaviors during your life.

This book is copyrighted under Creative Commons Attribution-NonCommercial 4.0 International Public License, which means that it’s free for you and anyone to use. The Fall 2020 edition is a substantial expansion of another edition written in the Fall of 2019, and will continue to be updated in the future.

1.1 The Plan for this book

This book encompasses 1) the development of a research project and 2) the analysis of the resulting data you might collect.

The first half of the book concentrates on the development of a research project. That half of the book is written for a student that has to write a class research paper or thesis and doesn’t know where to start. It’ll walk the student through the development and identification of an idea through the collection of data.

But just collecting data isn’t enough if you’re going to do your own research. And with the growth of data that is available online, it isn’t even a necessary place to start (although understanding the first half is important), So the second half is written with the idea that the data is collected, and now it must be analyzed. In those chapters the book will walk the reader through basic steps of presenting and analyzing data that are common to many research projects. In those chapters we’ll also learn how to do all of that in R, a free software that is commonly used in data science. We’ll talk about that more later though.

1.2 Acknowledgements

I’d like to thank several students that helped with the updating of this book: Theresa Anderson, Maria Andrade, Derek Brumfield, Diane Buckley, Ashley Felan, Britain Forsyth, Omar Garcia, Marcus Gibson, Heather Glass, Ashley Hebert, Kirstie Jiles, Alisha Large, Liz Mexwell, Todd McConnell, Tokolongo Mokuena, Ashley Paratore, Chad Populis, Ben Quimby, Sabrina Richardson, Stephanie Riegel, Frank Robertson, Michelle Rosamond, and Tosha Shanableh. Of course, any errors or mistakes are the authors alone.

I’d also like to thank Jesse Lecy for pushing me to learn R and inspiring me to put together this book.

Regional fertility predictors based on socioeconomic determinants in Slovakia

Original Research
Open access
Published: 02 July 2024
Volume 41 , article number 20 , ( 2024 )

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Janetta Nestorová Dická ORCID: orcid.org/0000-0003-1027-6871 1 &
Filip Lipták 1

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The study's primary purpose was to recognise the effects of determinants on the level of fertility and thereby explain the differences in trends in the regions of Slovakia. At the turn of the century, the differences in fertility in regions increased, but the total fertility rate decreased. Multivariate statistical methods clarified the regional effects of the level and nature of fertility. Initial regression surveys indicated weak effects between regions, which led to applying factor and cluster analysis to establish regional types. Comprehensive regression analysis was then applied. The strength and nature of regional relationships differed at the inter- and intra-regional levels. Research has demonstrated significant differences in fertility rates dependent on the socioeconomic environment, as regional types uniquely link to determinants. Moreover, each determinant has specific spatial patterns with unequal regression coefficients at different regional levels, which cannot be evaluated constantly. Knowing how spatial variation in fecundity occurs will enable future studies to elucidate the processes involved. Finally, fertility is vital for social assessment and policy formulation, the study’s findings could inform local decision-makers and planners in identifying the socioeconomic conditions underlying fertility at the regional level and planning appropriate intervention strategies.

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Avoid common mistakes on your manuscript.

Introduction

Like many other post-communist countries, Slovakia experienced a fertility transition in the early 1990s, achieving stable fertility below the replacement level. However, while differences in regional fertility levels increased at the turn of the century, the total fertility rate (TFR) decreased significantly. The TFR dropped from 2.1 in the early 1990s to 1.2 children per woman in the early 2000s. As a common phenomenon in post-communist countries, this trend has been the focus of much research. This study, in particular, aims to contribute to understanding this trend in Slovakia, where fertility is slowly increasing but remains below the replacement level, currently standing at 1.6 children per woman.

The political changes in Eastern and Central Europe at the end of the 1990s profoundly impacted various societal levels. The socialist system, seemingly stable and stagnant, was replaced by unprecedented social and economic changes (Sobotka, 2011 ). The establishment of democracy and the transformation of the Slovak economy led to the privatisation of state property and the restoration of private property and business. The emergence of unemployment and the fundamental changes in housing and family policy created a sense of social insecurity. Ultimately, these societal changes heralded ideological and cultural change, significantly altering population reproduction.

The previous socialist conditions had ensured a high degree of reproduction uniformity. It was especially noted in early fertility, a strong inclination towards the two-child family model, and low childlessness. Šprocha and Tišliar ( 2016 ) noted that in the post-communist period, due to societal changes, divergent tendencies are manifested in this area, and the reproductive paths of women differ. In addition, Potančoková ( 2011 ) reported that the significant factors affecting birth rates in the transformation period were decreased fertility intensity, childbirth postponement, and more children borne out of marriage. The power of these tendencies varied across Slovak regions due to differences in demographic, economic, social, and cultural factors. However, there is general agreement that these factors indirectly but significantly affect current fertility characteristics and inter-regional differences (Abdennadher et al., 2022 ; Campisi et al., 2020 ; Iwasaki & Kumo, 2020 ; Lieming et al., 2022 ).

The study evaluates the effects of socioeconomic determinants of fertility, explaining differences between regions in Slovakia. The regional fertility in Slovakia varies significantly. Herein, we identify significant fertility predictors based on regional strengths and characteristics. The study's originality lies in finding significant predictors behind the fertility rates between the regions of Slovakia while connecting the spatial context with the determinants explaining the differences.

Theoretical framework

Demographic development is a multidimensional process influenced by a combination of factors, and their interactions may vary in different regions and periods. Scientists from various fields have investigated the complex interplay of factors that shape demographic trends and changes in population composition (Bongaarts, 2009 ; Bontje, 2020 ; Pampel, 2011 ; Raymo, 2015 ; Sobotka & Fürnkranz-Prskawetz, 2020 ; Tulchinsky & Varavikova, 2014 ). Birth rates and fertility intensity are critical demographic components that determine population increase or decrease, and determinants with varying effects influence the levels. In addition, the set and structure of fertility determinants differ in countries and regional areas depending on the specific cultural, social, political, and economic situation. Moreover, the determinants interact and vary in relative importance in different contexts, so understanding specific population dynamics is crucial in establishing fertility and birth patterns.

Determinants affecting natality and fertility can be perceived in several broader categories (El-Ghannam, 2005 ; Marenčaková, 2006 ; Adhikari, 2010 ; Wang & Sun, 2016 ), while in the conditions of the Slovak regional structure, the level of fertility varies most often depending on social, economic or cultural factors (Potančoková et al., 2008 ; Šprocha & Bačík, 2021a , 2021b ; Šprocha & Bleha, 2018 ; Šprocha & Tišliar, 2019 ; Šprocha et al., 2022 ).

Sociocultural conditions

Sociocultural conditions may contribute to regional variation in fertility levels by influencing individuals living in certain areas. A major societal shift in Slovakia in the past three decades is increased women's education, and its association with fertility has been extensively researched. Results indicate that increased education is consistently related to lower TFR values (Adsera, 2017 ; Cheng et al., 2022 ; Gray & Evans, 2019 ; Maulida et al., 2023 ; Shirahase, 2000 ). Šprocha and Tišliar ( 2019 ) add that education is one of the critical factors in the intensity and timing of maternity and family starts and the realisation of fertility outcomes in Slovakia.

D'Addio and D'Ercole ( 2005 ) explained observed changes in OECD countries’ fertility rates by socio-economic influences, stating that as a result of increasing women's education, women's participation in the labor market also increases, the average age of first-time mothers increases, and women's higher education contributed to higher contraceptive use. More educated women are also more likely to delay childbearing until an older age because they participate in the labor market, are more economically independent, are more likely to have a career orientation and build a job position. Consequently, they often have fewer children than initially planned (Ní Brolcháin & Beaujouan, 2012 ; Iacovou & Tavares, 2011 ; Testa, 2014 ). The desire for children increases at higher income levels, increasing the chances of providing for a bigger family, and higher income, as well as better employment prospects, are the result of accumulated human capital in the form of higher educational attainment.

Becker ( 1992 ) assumes that people with higher education might want to have a larger number of children, thus pointing to the positive effect of income—but this is in contrast to the negative effect of the costs of lost opportunities (Nisén, 2016 ). However, age is a crucial determinant of fertility because conception ability decreases with age. Fekiačová ( 2019 ) adds that postponing parenthood until an older age can negatively affect the intensity of fertility in highly educated women in the form of a smaller number of children, or it can lead to final childlessness, which may indicate lower TFR values in the region. The opposite trend can be observed among less educated women when they enter motherhood soon after completing their education, thereby trying to reduce the uncertainty associated with the official labor market (Hechter & Kanazawa, 1997 ). In addition, Potančoková et al. ( 2008 ) cite ethnicity and cultural determinants of fertility, where Slovak Roma women with low education secure a more certain source of finance, which often indicates higher TFR values.

Further research provides evidence of an unequal relationship between education and fertility. The negative gradient dominates primarily in Central and Eastern European and German-speaking countries (Beaujouan et al., 2016 ; Klesment et al., 2014 ; Nisén et al., 2021 ; Wood et al., 2014 ). Deviations from this pattern have been reported in northern and northwestern European states (except Finland), where the gradients have narrowed and are often no longer observable (Jalovaara et al., 2019 ; Testa, 2014 ).

The theory of gender equality (Anderson & Kohler, 2015 ; McDonald, 2013 ; Mills, 2010 ; Neyer et al., 2013 ) also points out the negative impact of women's higher education on their fertility. However, the effect is not uniform and varies by gender and parity. The demographic revolution theory further elucidates the relationship between education and fertility (Axinn & Barber, 2001 ; Lesthaeghe, 2014 ; Sobotka et al., 2008 ). As women's educational attainment increases, fertility rates tend to decline, often associated with improved gender equality and socio-economic development in many developed countries.

Religiosity, explaining deviations in reproductive outcomes, has long been perceived as one of the significant and consistent factors determining actual fertility, especially in Slovakia (Šprocha & Tišliar, 2019 ). Numerous studies confirm its positive influence on fertility (Philipov & Berghammer, 2007 ; Frejka & Westoff, 2008 ; Zhang, 2008 ; Dilgmaghani, 2019 ; Herzer, 2019 ; Götmark & Andersson, 2020 ; Bein et al., 2021a ; Buber-Ennser & Berghammer, 2021 ). All religiosity rates are generally related to a higher ideal number of children, a higher probability of having another child, and a higher expected and actual number of children, primarily with the Catholic faith in the European environment. Among various dimensions of religiosity, religious involvement is a more significant predictor of fertility than religious tradition, affiliation, and self-rated religiousness (Philipov & Berghammer, 2007 ; Dilmaghani, 2019 ; Bein et al., 2021b ; Perry & Schleiffer, 2019 ; Buber-Ennser & Berghammer, 2021 ), which promises higher TFR values.

The scientific community has focused on clarifying the relationship between religion and fertility, and on explaining the differences in its influence on fertility in different countries. For example, religion is important in the lives of half of American women but in less than one-sixth of European women. In addition, Frejka and Westoff ( 2008 ) report that women in Northern and Western Europe are less religious. However, they have the same or even higher fertility than American women, and significantly higher fertility than Southern European women. The authors consider that a slight increase in European fertility could theoretically be expected if Europeans were as religious as Americans. Buber-Ennser and Berghammer ( 2021 ) add that the positive influence of religion on actual fertility outcomes is much more substantial in Western Europe than in Central and Eastern Europe. Moreover, the effects of religion in the latter countries are considered generally weak and inconsistent, and religious significance and relationship to fertility there would benefit from further investigation.

Many studies have examined variations in fertility levels in different ethnicities (Adebowale, 2019 ; Bagavos et al., 2008 ; Booth, 2010 ; Chui & Trovata, 1989 ; Dubuc & Haskey, 2010 ; Forste & Tienda, 1996 ; Jasilioniene et al., 2014 ; Martin, 2019 ; Muhammad, 1996 ; Urale et al., 2019 ), which explain in connection with cultural, social, economic and minority postulates. Some ethnic and cultural groups maintain relatively high birth rates despite the global shift towards smaller families, and traditional gender roles, religious beliefs, cultural norms, and socio-economic conditions all influence the outcome. Moreover, established patterns are not absolute determinants because individual choices and circumstances vary considerably within a given ethnic group (Forste & Tienda, 1996 ; Majo, 2014 ; Šprocha, 2014 ).

Another important differentiating factor in fertility outcomes is marital status, which affects basic demographic processes such as birth rate and mortality, as well as marriage and abortion rates. Concerning fertility, marriage has long been considered its prerequisite (Ridfuss & Parnell, 1989 ), and their high degree of correlation in the past has been empirically documented (Magdalenić, 2016 ). However, with the onset of the demographic transition, this relationship began to loosen, and new forms of family behavior appeared in society. Several studies have led to the clarification of the relationship between marital status and fertility and the description of differences in the level of fertility between subpopulations with different marital status (Van Bavel et al., 2012 ; Hiekel & Castro-Martín, 2014 ; Magdalenić, 2016 ; Meggiolaro & Ongaro, 2010 ; Nedomová, 2015 ; Perelli-Harris et al., 2009 ; 2014 ; Perelli-Harris, 2014 ; Raley, 2001 ; Ridfuss & Parnell, 1989 ). Behind the increase in non-marital births in the European area is an increasing number of conceptions and births within cohabitation, pointed out by Perelli-Harris et al. ( 2012 ), while in most of the observed countries, the percentage of births to unmarried women decreased or remained relatively similar. According to Magdalenić ( 2016 ), the reproductive function of marriage thus loses its relevance. In addition to the type of partnership itself, fertility is also affected by its instability. In line with Meggiolaro and Ongaro ( 2010 ), divorce can theoretically be considered a depressive factor, but empirical studies have not consistently confirmed this hypothesis. Remarriage and cohabitation increase the probability of giving birth after the dissolution of marriage, whereby separated childless women have a higher risk of conception. However, according to Van Bavel et al. ( 2012 ), divorced women have lower fertility than continuously married women, even when re-partnering. In the case of men, it is the opposite.

Slovakia also captures something similar, where with the onset of the second demographic transition (cf. Mládek, 1998 ) already in the early 1990s, new forms of family behavior begin to appear with a gradual decline in cohabitation in marriage and an increase in partnerships cohabitation. The period of the last three decades due to population aging (Kačerová, 2009 ; Šprocha & Ďurček, 2019 ) also brings changes in the age composition of the Slovak population due to population aging (Kačerová, 2009 ; Šprocha & Ďurček, 2019 ) with the expansion of thirty- and forty-year-old age groups, which enters into marriage more often. These changes are behind the significant increase in the share of the reproductive Slovak population living in marriage and only a slight increase in the divorced. Up to 85% of the population lived in marriages in Slovakia in the last census of 2021, and 17% of the reproductive population were divorced. Among the EU countries, Slovakia still has a higher proportion of married people. The shift in society from the traditional model of the family, which typically involved a married couple and their children living together, to modern and postmodern forms of family relations with an inclination towards individualism, personal freedom, and independence (Kraus et al., 2020 ; Mendelová, 2018 ) causes a general decline in marital cohabitation with the prospect of further decline, then would be the relevance of using the women's divorce rate in the research low.

Nevertheless, within the demographic of reproductive-aged women, married Slovak women continue to outnumber divorced women, with a notable correlation observed between Slovak regions and TFR. Šprocha and Tišliar ( 2021 ) also indicate that middle-aged and older women enter the marriage union, where the union remains more stable if women with a higher education who postpone motherhood enter it. However, many factors influence the formation of the regional structure of the reproductive population according to family status. Demographic factors include primarily the intensity and timing of marriage and divorce. Therefore, in the north and east of Slovakia, a region with a more significant representation of married women was formed (cf. Bleha et al., 2014 ). In the western region, it is precisely the hinterland of the capital city that, due to the migration attraction of the productive population, registered a similarly higher proportion of married women in the last period (cf. Pregi & Novotný, 2019 ). The southern region of Slovakia is represented by a higher representation of cohabitation and a higher representation of divorced women in the reproductive population, which some authors (Džupinová et al., 2008 ; Korec, 2005 ; Šprocha & Ďurček, 2017 ) explain by a higher representation of low-income persons, higher unemployment and a lower level of development of local economies.

Economic conditions

The income-fertility hypothesis describing the relationship between income and fertility suggests that fertility falls as income rises. D'Addio and D'Ercole ( 2005 ) consider women's income and earnings as critical influences for childbearing, and they record the complexity of the relationship between income and fertility. Findings have shown that fertility rates can reflect the difference between current and past income levels of each cohort, and wealthier OECD countries have higher fertility rates and higher average age at first birth (Herzer et al., 2012 ), while in all countries, women with higher household income levels have fewer children compared to other women. Although there is a general correlation between income and fertility, this relationship can vary across countries and cultures (Fox et al., 2019 ; Luci-Greulich & Thévenon, 2014 ).

Individual preferences and choices regarding family size can differ significantly, even within income groups. Shifts in family policies (Adema & Thévenon, 2014 ), changes in the spatial organization of the economic sphere (Ciminelli et al., 2021 ; Wachsmuth, 2022 ), and selective processes of international and internal migration (Rees et al., 2017 ; Billari & Dalla Zuana, 2013 ; Pregi & Novotný, 2019 ) contribute to this. In addition, Fox et al. ( 2019 ) suggest a stronger convex relationship between fertility and income in Western European countries, while in Eastern European countries, where only Poland and the Slovak Republic seem to have transitioned to a positive fertility–income relationship.. The income level at which the association between income and fertility changes from negative to positive was much lower in the East than in the West but varied in both regions.

Some research has documented an inverse relationship between fertility rates and women's participation in the labor market (see Bernhardt, 1993 ; Mishra & Smyth, 2010 ; Altuzarra et al., 2019 ; Del Rey et al., 2021 ). However, some studies point to a change in the correlation between total fertility and the women's employment rate or the labor force participation rate (Ahn & Mira, 2002 ; D'Addio & D'Ercole, 2005 ; Del Boca et al., 2003 ) or they track their joint growth (Hwang et al., 2018 ) in some OECD countries. In fact, according to Klasen et al. ( 2021 ), heterogeneity in returns to women’s own characteristics and family circumstances—including education, income, and fertility explains most of the between-country differences in participation rates, indicating that the economic, social, and institutional constraints that shape women’s labor force participation are still largely country-specific.

Hwang et al. ( 2018 ) see the change in correlation and the increase in both indicators as an increase in childcare substitutability, i.e. the degree of perception of market-provided child care by parents as a sufficient substitute for the mother’s time. As the value of substitutability increases, the female labor force participation rate increases while a convex relationship (U-shaped) emerges in interaction with TFR, the existence of which can be explained by a combination of behavioral and compositional effects. According to Thévenon and Luci ( 2012 ), fertility trends also depend decisively on mothers' ability to combine work and family life, pointing to a higher fertility rate in countries where women have greater access to the labor market (Northern European countries and France). Fertility outcomes can be influenced by the availability of formal childcare facilities, which (Ridfuss et al., 2010 ; Haan & Wrohlich, 2011 ) is considered an essential prenatal tool of family policy mitigating the conflict between work and family. Jung et al. ( 2019 ), as well as Wood and Neels ( 2019 ), state that despite the generally widespread hypothesis about the positive impact of available childcare on the level of fertility in the developed world, the results of several empirical studies are ambiguous and contrary to hypothetical expectations. A positive relationship between these indicators was recorded most often only in regions with high participation of women in the labor market. However, the research results of Ridfuss et al. ( 2010 ) showed that increasing the availability, i.e., capacity, of facilities from 0 to 60% for preschool children in Norway led to an increase in fertility by 0.5–0.7 children per woman under 35 years of age.

In addition to women's participation in the labor market, unemployment also affects the timing and intensity of fertility. Still, according to some authors, the effects are unclear (Andersen & Özcan, 2021 ; Bono et al., 2015 ; Huttunen & Kellokumpu, 2016 ). D'Addio and D'Ercole ( 2005 ) point out that in the 1990s, there was a change in the correlation between fertility and unemployment, with the fertility rate of most OECD countries being higher in times of low unemployment and falling with its increase. Adsera ( 2011 ) states that high and persistent unemployment is associated with delayed childbearing and, as a result, likely fewer children. However, Fernandez-Crehuet et al. ( 2020 ) report that fertility and unemployment rates are unrelated in the long run. Andersen and Özcan ( 2021 ) also concluded that unemployment positively affects the transition to motherhood and has no significant effect on second-order children, possibly due to the specificity of the Danish context. Finally, studies record that unemployment does not necessarily negatively affect fertility, and its negative impact is selective.

Housing availability further determines fertility, but its influence in Slovakia has rarely been analyzed. However, Katuša ( 2012 ) demonstrated that many young Slovak couples could not afford appropriate housing for child-rearing, and this was a prominent cause of the decline in birth rates and fertility, regardless of employment, education status, and other factors. European researchers (Campisi et al., 2020 ; Makszin & Bohle, 2020 ; Mulder & Billari, 2006 ; Stoenchev & Hrischeva, 2023 ; Zavisca & Gerber, 2016 ) have led efforts to understand how housing conditions, especially ownership, are related to the transition to adulthood, the formation and dissolution of partnerships, and fertility.

In addition, Zavisca and Gerber ( 2016 ) identified housing as a primary source of socioeconomic difference, with the home critical for everyday life and family dynamics, consumer lifestyle, subjective well-being, and family planning. High housing prices also mean that individuals and couples may face financial constraints that make it difficult to afford the costs associated with raising children. According to studies by Zhang et al. ( 2012 ) and Saguin ( 2021 ), an increase in housing prices leads to an indistinctive decrease in the birth rate, but changes in housing prices do not have an immediate effect on fertility; they can even also have a positive impact (Clark & Ferrer, 2019 ; Simo-Kengne & Bonga-Bonga, 2020 ). However, housing availability problems affect the timing of births more significantly than the intensity of fertility (Kostelecký & Vobecká, 2009 ), and the relationship between housing affordability and fertility, therefore, varies depending on the region or country’s social, economic, and cultural background.

Urban–rural conditions

The degree of urbanization similarly plays a role in the fertility rates. Urban areas tend to have a higher prevalence of apartments with smaller living spaces, which is natural due to population density and limited land availability. Research by Kulu and Vikat ( 2007 ) revealed that people living in apartments have lower fertility than those living in single-family homes. The smaller living spaces of housing may force families to limit childbearing due to space constraints. In contrast, the family environment often associated with family houses may facilitate reproduction in rural areas (Felson & Solaún, 1975 ).

High housing costs can lead individuals to migrate from urban centers to rural or suburban environments, where they can generally have more children. These selective steps for increasing fertility outcomes may also contribute to patterns of low urban fertility (Kulu, 2013 ; Rusterholz, 2015 ). However, studies also show that selective moves from urban centers to family-friendly environments do not cause significant differences in urban–rural fertility levels (Kulu & Washbrook, 2014 ).

Marenčáková ( 2001 ) considers the size of the settlement to be an important differentiating factor for several demographic phenomena and processes in Slovakia and adds that the difference in the reproductive behavior of the population of cities and rural communities is generally accepted. Scientific studies (Kulu & Boyle, 2009 ; Vobecká & Piguet, 2012 ; Kulu, 2013 ; Kulu & Washbrook, 2014 ; Riederer & Buber-Ennser, 2019 ; Lopéz-Gay & Salvati, 2021 ; Rodrigo-Comino et al., 2021 ; Salvati, 2021 ) describe and explain the differences in fertility levels based on the urban–rural dichotomy or along the city-suburb-rural gradient. Most confirm that rural areas and small towns have higher fertility than large cities. Urban–rural fertility disparities decrease over time (Bleha et al., 2020 ; Kulu, 2013 ) when factors describing the economic environment, family and gender norms, and population composition are considered (Riederer& Beaujouan, 2024 ).

While urbanization generally correlates with lower birth rates, there can be considerable variation between countries and regions. According to Billari and Kohler et al. ( 2002 ), European regional fertility regimes have rapidly changed due to common socio-economic transformations. However, these changes vary across the geographical gradient north–south and west–east of European cities (Rodrigo-Comino et al., 2021 ). These findings largely mirror the dominant phase of the urban life cycle (Morelli et al., 2014 ). Northwestern cities have entered a phase of reurbanization (Dembski et al., 2021 ), leading to new forms of urban expansion such as polycentric development. This trend has seen inner cores gradually attracting a younger population and couples with a high propensity to marry and have children, indirectly contributing to a higher average birth rate.

Conversely, Eastern European cities are still undergoing the final phase of suburbanization (Stryjakiewicz, 2022 ; Szmytkie, 2021 ), characterized by intense population growth in suburban districts and significant stability or even shrinkage of inner urban cores. Rodrigo-Comino et al. ( 2021 ) state that suburbanization is only associated with younger and larger families—and thus higher fertility levels—in Eastern and Southern Europe. Compositional and contextual factors and the influence of selective migration and housing conditions can explain differences in fertility between urban and rural areas (Kulu, 2013 ; Kulu & Washbrook, 2014 ; Nestorová Dická et al., 2019 ; Riederer & Buber-Ennser, 2019 ).

Other conditions

The theoretical overview of the factors that influence the level of regional fertility indicates the authors' intention to include them in their research. However, in addition to the above, regional fertility can be conditioned by other indicators not included in our study. Studies, such as Hesketh and Xing ( 2006 ), Wu et al. ( 2006 ), Tafuro and Guilmoto ( 2020 ), Chao et al. ( 2021 ), and Becquet et al. ( 2022 ), have pointed out that the gender ratio of the reproductive population can also play an important role in the given issue. Slovakia's secondary sex ratio shows a slight predominance of the male gender, similar to the case in other developed regions (Orzack et al., 2015 ), which can be used as a reflection of living conditions and health status (Chao et al., 2022 ) while deteriorating conditions are associated with a decrease in ratio values and vice versa. Golian and Liczbińska ( 2022 ) also confirmed what was stated for Slovakian conditions, while in the period of formation of the current reproductive population, there are no significant exogenous shocks that could significantly affect the sex ratio at birth and thereby affect the demographic status of the current reproductive populations in the regions of Slovakia. In almost every region of Slovakia, men slightly predominate in the reproductive population, or the ratio is mainly balanced. In the end, even the initial survey of the relationship between the fertile population of women and the level of fertility between Slovak regions did not confirm significance.

However, the migration factor can also affect the total fertility rate. In regions with significant migration, the birth rate can be affected by changes in the population's demographic composition (e.g., Bagavos, 2019 ; Sabater & Graham, 2019 ). In Europe, some authors register that economic and migration factors often explain changes in fertility (cf. Majelantle & Navaneetham, 2013 ; Sobotka et al., 2011 ), and migration may be responsible for reshaping the ethnic and social composition of many highly developed countries (Sobotka, 2008 ). According to research by Parr ( 2021 ) on the fertility replacement level in the presence of positive net immigration, Slovakia's current migration replacement TFR is low. This is related to its low birth rate and low net migration, and the relatively lower life expectancy at birth also plays a role compared to Western, more developed countries. This means that migration does not significantly impact the overall demographic situation in the Slovak regions and, therefore, not on the level of fertility. Compared to Western, more developed countries, where migration can be a more significant factor, its influence is minimal in Slovakia. As for life expectancy, although it is relatively lower compared to Western countries and may affect the demographic structure of the population, it does not directly affect the fertility rate. Fertility levels are more influenced by other social, economic, and cultural factors, which are the primary focus of our research.

In the same way, access to health care plays an important role in the issue of this research. Regions with better access to health facilities and information on reproductive health tend to have lower fertility due to increased use of contraception and better outcomes in the area of maternal health, as confirmed by studies such as Yüceşahin and Özgür ( 2008 ), Phillips et al. ( 2019 ), Herrera-Almanza and Rosales-Rueda ( 2020 ). From another point of view, according to Brodeur et al. ( 2022 ) and Jones et al. ( 2023 ), access to reproductive health care services, including family planning resources and prenatal care, can affect fertility rates. Stefko et al. ( 2018 ) demonstrated the diversity of healthcare facilities' performance in Slovakia's regions. However, over time, there is an indirect dependence between the variables and the results of the estimated efficiency in all regions, and thus, all regions of Slovakia have increased their productivity compared to ten years before the COVID-19 pandemic. Technological improvements significantly impacted this improvement (Vaňková & Vrabková, 2022 ). Even though Soltes ( 2016 ) states that the situation in individual regions is uneven and there are regional differences in access to care, all Slovak districts have medical facilities of varying quality. It is important to note that access to health care can affect a population's overall health, but the direct effect on fertility levels is unclear. Our research focused on other factors that directly and significantly impact fertility levels, such as economic, social, and cultural determinants. Although access to health care is important for the population's overall health status, based on available data and research, it was not considered a key factor that would directly influence the fertility rate in Slovak regions.

In addition to the determinants mentioned above, the researchers also investigated the relationship between abortion, average life expectancy (Trynov et al., 2020 ), the size of the university population, the share of employees in agriculture (Campisi et al., 2020 ), or also investigating the quality of life and the level of fertility (Palomba et al., 2018 ; Koert, 2021 ). These factors play a significant or less significant role in influencing overall fertility in the regions.

Abortion rates can have an impact on the level of fertility in Slovak regions, but this relationship is often complex and influenced by many other determinants that influence reproductive behavior. In our research, we focused on identifying factors that directly and significantly affect the level of fertility. In the initial phase of the investigation, no significant relationship between abortion rate and fertility level was demonstrated. This confirmed that abortion is not the primary determinant of fertility in Slovak regions in the context of our research.

Educating women plays a significant role in the final level of fertility. Research indicates that women's low education is directly linked to a higher fertility rate (cf. Šprocha et al., 2020 ). Although higher education also affects fertility, its effect may be more indirect and complex. Higher education is often associated with postponing parenthood, lower fertility rates, and greater emphasis on career and personal development (Šprocha & Bačík, 2021a , 2021b ). As part of our research, we decided to focus on women's low education because its impact on fertility is more direct and pronounced in the context of Slovakia.

The level of employment in agriculture indicates a society's development level, which can impact the overall fertility level. Less developed regions often show higher fertility rates, influenced by various social and cultural factors. However, in the case of Slovakia, employment in agriculture is very low, representing only 2% of the economically active population, and this share does not differ significantly in individual regions. Although theoretically, higher employment in agriculture can be related to higher fertility, empirical data for Slovakia do not confirm this relationship. Based on the analysis of regional differences, we found that higher employment in agriculture does not automatically mean higher female fertility. Therefore, we decided not to include this factor in our research because it would not contribute to a more accurate understanding of the determinants of fertility in Slovak regions.

The influence of quality of life on fertility is complex and may vary according to specific conditions in a given country or region. A higher quality of life can lead to lower fertility due to better economic stability, higher education, and better access to health care. Conversely, lower quality of life may be associated with higher fertility due to traditional values and lower access to contraception and health care. In our research, however, we found that the quality of life factor penetrates our analyzed social, economic, and cultural determinants of fertility. Specifically, we considered different aspects of quality of life within these determinants, such as economic stability, education, and access to health care, and analyzed their individual impact on fertility levels. Therefore, we decided not to include quality of life as a separate factor but rather to integrate its various aspects into the broader context of our research.

Research focus

To understand what drives the differences in the rate of participation in fertility in the regions at the beginning of the twenty-first century, we create a unified empirical framework that enables comparative analyses in space Slovakia. The research goal is to recognize the effects of socioeconomic determinants affecting fertility in the Slovak regions. This objective can only be investigated to the extent that the items in the last population census in Slovakia and the public databases of the Slovakian statistical office are available. Therefore, answers to how a region’s culture contributes to fertility may remain unanswered. Correlations between fertility rates and selected determinants may provide insight into some correlates or primary predictors of fertility in these groups. They may open avenues for further, more purposeful research into the difference in fertility levels in Slovak regions.

Data and methods

The study relies on publicly available statistics from the Statistical Office of the Slovak Republic (SOSR) and the Center for Scientific and Technical Information of the Slovak Republic (CSTI SR). The primary determinants are selected indicators from the demographic, social, and economic statistics in the public DATAcube database. The primary database consisted of data on women’s birth rate and fertility, followed by data on the unemployment rate of women, the average monthly income, and the number of completed housing units. The second section of the statistical data includes key data about religion, nationality, women's family status, and women's education from the last population census in 2021.

The CSTI SR delivers data on the number of children, pupils, and students at various types of schools in the Slovak regions. Childcare substitutability in kindergartens for children aged 3–6 years was investigated concerning fertility levels and nature in Slovak regions. The last census revealed the ethnic structure of Slovakia's inhabitants, and this information was used to estimate the Roma population, which has significantly different reproductive behaviors (Nestorová Dická, 2021 ). Correcting this data with the Atlas of Roma Communities ( 2019 ) gave a reliable reality compared to the implemented state population censuses (Šprocha, 2014 ).

Spatial research was implemented at the LAU1 level, covering Slovak districts at the regional level. Bezák ( 1996 ) proposed merging the Bratislavan and Košice city districts in separate spatial units for research purposes. They were not integrated as part of the study of the determinants of fertility, and the existence of 9 urban districts of Bratislava and 22 urban districts of Košice was preserved due to their diversity in terms of birth rate and fertility of the population, as well as socioeconomic determinants.

The basic spatial units consisted of 79 districts, diverse in spatial and population size. For example, Prešov, Nitra, and Žilina districts have more than 160,000 inhabitants. In contrast, Stropkov, Turčianské Teplice, Banská Štiavnica, and Medzilaborce consist of less than 20,000 people. Bezák ( 1996 , 1997 ) pointed out Slovak regional inequality and injustice. The available data for regional analysis is only for these spatial units. Statistical analyses of women's fertility determinants provide ample opportunity to investigate socioeconomic effects in the aforementioned regional structure. The reference period for analyzing fertility data and selected determinants was 2019–2021, and the census data was from 2021.

Due to the primary purpose of the research, which is a regression analysis of the influence of socioeconomic determinants (Table 1 ) on the level of TFR fertility in the regions as a dependent variable, the key was the selection of determinants as independent variables, the choice of which was conditional on the results of many professional studies listed in the theoretical framework dealing with various socioeconomic effects on fertility.

Initial regression analysis of the influence of selected socioeconomic indicators in spatial units on the fertility level revealed only fragile dependencies, and the correlation strength with different indicators varied in some regions. The reason is significant regional diversity in terms of fertility and socioeconomic determinants.

That led us to create a regional typification of spatial units, where individual types are quasi-homogeneous sets of spatial units with similarities in fertility nature and level. Factor analysis (FA) was crucial for the typification of spatial units. It reduced the number of intercorrelated input variables without much information loss and created new variables, i.e., factors (Nestorová Dická, 2013 ). FA assumes that each entering trait can be expressed as a linear combination of a few common latent factors.

The input database consisted of 10 variables related to various aspects of fertility and fertility (Table 1 ). The rate of Kaiser–Meyer–Olkin (KMO; 0.83), which tests the suitability of input data for FA by comparing the size of experimental correlation coefficients to the size of partial correlation coefficients, evaluated the original input variables as highly suitable for FA.

The factor model with the Principal component analysis (PCA) method was aimed at identifying interrelated groups of variables. The PCA method is one of the most frequently used in FA, identifying linear combinations of observed variables that maximize the overall variability of the data. FA used the PCA method to extract the components from the reduced correlation matrix, in which FA monitored the initial estimates of the communalities of the individual variables. For FA, the most significant factors determined according to Kaiser's eigenvalue criterion, i.e., factors with an eigenvalue greater than one, are considered statistically significant. Two primary factors can thus clarify the structure and fertility level in Slovakia regions (Table 2 ), which explain almost 91% of the total variability of the input variables.

Extracted factors with factor scores for each spatial unit express the degree of influence of individual factors (Fig. 1 ). The mentioned factors became the basis for regional typification. Relatively homogeneous regional classes concerning fertility's nature and intensity due to applied cluster analysis were created (Fig. 2 ). Where spatial units were classified through a hierarchical procedure using Euclidean distances, to which Ward's clustering method applies. Finally, the discriminant cluster analysis results verified the optimal spatial unit distribution for the selected number of types. The 10 resultant regional types were entered into regression analysis of selected fertility determinants in Slovak regions (Fig. 2 and Table 3 ).

Extracted factors differentiating fertility nature and intensity in the Slovak regions

Regional typification of fertility nature and intensity

The second part of the research focused on the knowledge of the effects of socioeconomic determinants on fertility in individual regional types, i.e., using regression analysis at two hierarchical levels (see Götmark & Andersson, 2020 ). Research first established the relationship between individual regional types, i.e. the investigated units here represent unique regional types with average values of TFR and socioeconomic determinants. The second level represents investigation within individual regional types at the level of spatial units, i.e. the investigated units here represent regional-type spatial units with their values of TFR and socioeconomic determinants. All analysed regional types had equal weight. For each socioeconomic determinant, a regression trend, correlation, and determination coefficient R2 were obtained at both levels, which, according to Klein ( 2020 ), provides the level of total variability explained by the independent variable. The model is more "effective" if its value is closer to 1, meaning the linear regression model explains a larger percentage of variability. Řehák ( 2023 ) adds that the coefficient of determination also represents a measure of statistical dependence between the independent and dependent variables, and its higher value indicates closer statistical dependence. The value of R2 expresses dependency strength, and the value of the coefficient β1 the character of the influence in the linear Eq. ( 1 ). A positive coefficient is established when Y increases as X increases, and negative values indicate an indirect effect. A linear regression model at the intraregional level was applied only for regional types containing more than one spatial unit.

In the final phase of the investigation, the effects determinants of regional fertility were detected using the multiple linear regression method (MLR). The MLR evaluated the relationship between a continuous target, i.e., the factors from factorial analysis, and selected 9 socioeconomic determinants. The multiple regression model is developed from a simple regression model, where the dependent variable Y is a function of several independent variables X1, X2, X3,…, X9, and the residual component (error terms). The study uses an equation model (2), with Y as the dependent variable, X as the independent variable(s), β0 is the point where the regression line intersects the Y axis, β1 to β9 are the regression coefficients that determine the direction of the line, and e is the measurement error. After controlling for the effect of other predictors, the net effect of each independent variable on the dependent variable has also been measured through multivariate analysis MLR.

As a post-communist country, Slovakia has had an insufficient level of fertility below the replacement rate since the beginning of the 1990s. Although some authors (cf. Šprocha & Bačík, 2021a , 2021b ; Šprocha & Tišliar, 2016 ) emphasized the partial reversal of development trends during the new millennium, its increased level remains below the replacement rate, while the spatial picture of fertility in Slovakia is changing. Figure 3 highlights the spatial distribution of TFR values and fertility timing in Slovakia regions. A key factor in the spatial variability of fertility in Slovakia is the advanced process of postponing childbearing. Closely linked with it are indicators of the timing and age distribution of fertility, which contribute to the current differentiation of regions (Fig. 3 ). The existence of significant differences in the intensity and timing of fertility was also confirmed by studies such as Bleha et al. ( 2014 ), Šídlo and Šprocha ( 2018 ), Šprocha et al. ( 2019 ). During the new millennium, a vast region with very low fertility was formed in Slovakia, located in Slovakia's western and easternmost areas. The processes of postponing childbearing mark the districts of this region, and therefore, by a significant increase in fertility at an older age, and according to Šprocha et al. ( 2019 ), only by a very limited catch-up rate. Moreover, the capital region is forming an area with relatively favorable recuperation phase development. The region with a favorable level of fertility, a significantly smaller area, occupies areas in the middle east and north of Slovakia, in which the favorable level of fertility is a reflection of specific socio-demographic features (cf. Drinka & Majo, 2016 ; Nestorová Dická, 2021 ; Roupa & Kusendová, 2013 ).

Source: SO SR

Total fertility rate and timing of fertility in Slovakia regions, 2019–2021.

Factorial analysis and regional typification

The two factors extracted from factor analysis are independent variables with special links to human fertility nature and level in the Slovak regions. Figure 1 highlights the spatial distribution of factor scores and the relationship of regions to both generated fertility factors.

The first factor has a significant relation to indicators pointing to the age distribution of fertility, including the fertility of higher-order children and non-marital fertility; it can be interpreted as a factor in fertility timing, cohabitation, and family size. The factor covered up to 49% of the total variance of the variables. From a spatial perspective, the country's eastern region, particularly its southern and partly northern areas, exhibits a higher prevalence of fertility among younger women, along with increased rates of cohabitation and higher-order childbearing (Fig. 1 ). A peripheral location, underdeveloped economies with high long-term unemployment rates, inadequate or absent transport infrastructure, and lower human potential characterize regions. This is primarily evidenced by a low proportion of the population with higher education, a high proportion of residents from socially excluded environments, and marginalized Roma communities. The earlier onset of fertility, coupled with a higher prevalence of children born out of wedlock and in higher order in these regions, may be attributed to attempts to mitigate the financial uncertainty associated with the labor market (Potančoková et al., 2008 ) and ensure at least a certain income in unfavorable structural conditions, thanks to which the costs of lost opportunities related to childcare are low (Šprocha & Tišliar, 2019 ). In contrast, the North-Western geographical regions are prosperous and attractive to a higher-income population. The postponement of childbearing can be explained by the higher participation of women in the labor market; their higher education offers greater career prospects and economic independence in the labor market with building a job position (NíBrolcháina & Beaujouana, 2012 ), as a result, the costs of lost opportunities are high.

The second factor expresses the intensity of fertility, and it covers 42% of the total variability in the input information. Low and insufficient fertility, well below the replacement rate, is typical for many regions in the extreme east or west, south or central part of Slovakia (Fig. 1 ). Ethnic, cultural, and economic factors determine the higher intensity of fertility. Behind the low intensity of fertility can be peripherality or rurality (Nestorová Dická et al., 2019 ), bad economic situation, and a greater concentration of the population without religion or belonging to Protestant denominations. Finally, these communities generally have lower fertility levels, and often a higher percentage of the aged population.

Fertility regional typification in Slovakia was created by combining the obtained factor score levels. Figure 2 shows the ten regional types generated by cluster analysis, representing the different structures of human fertility and natality. Regional types A to E reflect low fertility and natality, with older women's more intensive fertility. They occupy the far east of Slovakia and the western region, except the capital region. Regional types F to J, which have higher fertility levels, represent the opposite. They are found in the central part of eastern Slovakia and the north. The positive extreme is represented by regional type J, which reached a higher fertility level above the replacement rate, with the fertility of primarily younger women and a higher birth rate of children of higher order. Its existence is connected with the Roma population, which has a significant presence mainly in the central part of eastern Slovakia. In contrast, the negative extreme is represented by region A, which has the lowest-low fertility according to the designation fertility levels by Kohler et al. ( 2002 ) and occupies Slovak districts primarily in the far east and western parts of the country.

The regression analysis applied to previous research results (regional types) established the effect of selected socioeconomic determinants on fertility (TFR) at two hierarchical levels. Because the cluster analysis was used, the variation in TFR values was relatively low for individual regional types inside, i.e., at the intraregional level. TFR values varied somewhat more between districts in regions J and F. Higher variability is between average TFR values of individual types, i.e., at the interregional level. Regional types G and I represent the highest levels of TFR (2.4–2.3), but Types A to H registered TFR values well below the replacement rate.

The key findings of the relationship between selected socioeconomic determinants and TFR in regional types are documented in Fig. 4 . Regression analysis reveals that the fertility level of the population was negatively related primarily to the women's divorce rate, Childcare substitutability rate, urbanization, and monthly income at the interregional level. A positive trend was determined for the Roma ethnicity, the Catholic population, unemployment, and low education of women. However, residential building did not affect fertility. The women’s divorce rate had the closest relationship with fertility at R2 = 0.62 and Roma ethnicity at R2 = 0.44.

Total Fertility Rate (TFR) in Regional Types and its Relationship to Socioeconomic Determinants

Figures 2 and 4 highlight that regional type I, which represents only one district known for strong tradition, religious beliefs, and national unity with the low ethnic diversity of its population, records the lowest 3.7% average divorce rate with an extreme positive level of TFR. Type F, as the region of the capital with the hinterland, had the highest rate, with a value of up to 14%. The TFR is low below the replacement level. This stark contrast in divorce rates significantly impacts the TFR, which decreases with increasing divorce rates in regional types. On the contrary, the fertility level increased significantly with Roma ethnicity, where the average concentration of the Roma population varied from zero in types F and I to 8.1% in type J, where the TFR with a level of 2.3 children per woman represents the highest recorded value among the Slovak regions.

A significant correlation with TFR was also achieved with the degree of enrollment rate of children in kindergartens or the degree of urbanisation, while women's fertility decreases with their growth. The enrollment rate of children ranged from 535‰ in type J, with 2.3 children per woman, to 808‰ in type A, representing the lowest fertility level of 1.3. Similarly, it noted the indicator of urbanization, where values ranged from 12.3% in type I with a fertility level above the replacement rate to 82.7% in type F with a TFR of 1.6 children per woman. The amount of the monthly income also demonstrated a slight negative dependence. Research indicates that economically developed regions are directly related to a lower TFR. On the contrary, TFR values increased more significantly with the level of Catholicism and female unemployment. The proof is the generated types I and J, where the types reached the highest values of measures of Catholicism and simultaneously have the highest levels of TFR, i.e. more than 2.0 children. Regions dominated by the Protestant population record a lower TFR level below 1.5 children. Female unemployment was the lowest in the regional type of the capital city with hinterland (type F), with a value of 5.5%. The TFR of type F reached only 1.6 children per woman, and the highest fertility level, 2.3 children, was recorded in type J, with 20% of unemployed women.

From the point of view of the broader socioeconomic context, however, there are significant correlations also between the individual socioeconomic controls (Table 4 ) among the ten regional types. It was noted that the low educational level of women is significantly positively correlated with the Roma community, in which, at the same time, higher female unemployment persists with low monthly incomes, rates of children’s schooling, residential construction, or the rate of urbanization. The higher Roma community in regional types G, H, and J confirms higher unemployment and low incomes dominated by the rural population with a low level of residential development. The female divorce rate, on the other hand, indicates a significant relationship to urbanization with higher monthly incomes but with lower rates of Catholics, who are more likely to be concentrated in more rural regions. Residential construction primarily concerns regions with higher incomes, educational levels, and female employment. The aforementioned socioeconomic controls are documented by the Bratislava regional type F.

The TFR and socioeconomic determinant relation are also analyzed at the level of individual districts within regional types. Correlations between TFRs and socioeconomic determinants are present in Fig. 5 . However, the strength and nature of the relationships often differed from the previous level. Figures 4 and 5 highlight deviations in intraregional regression. We registered the most significant variations in four socioeconomic indicators. Prevailing opposite trends appear in the case of monthly income, Catholicism, and women's unemployment. On the other hand, residential building development showed a positive trend several times at the intraregional level, while independence was demonstrated only in one type, J. All regional types showed a negative association between TFR and urbanization, confirming the relationship reported in many studies.

Correlations between Total Fertility Rates and socioeconomic determinants

In five types, TFR increases with the increasing rate of women with low education, while this relationship is strongest in Bratislava type F. In five regions, the TFR decreases to the growing women's divorce rate, most in type C. Surprisingly, the opposite but significant trend was noted in type A. Regression analysis significantly and positively confirmed the association between fertility and Roma ethnicity in four types, but the relationship was negative in three.

Types C and F show a certain similarity in the observed trends, which, apart from the high intensity of dependence, differ only in the unemployment of women, where the opposite trends have taken place. Regional type D, significantly spatially disjointed with districts scattered throughout the country, did not capture a significant relationship to the given determinants.

Compared to the relationships found at the interregional level, no type showed complete similarity in the relationship of TRF to socioeconomic determinants. However, the most significant similarity was found in Bratislava type F, whose districts showed opposite trends only at Roma ethnicity and residential building. Regional type A shows significant differences, with confirmed tendency only in women's low education or the degree of childcare substitutability. The closeness of the relationships is not significant.

In assessing the intensity of the association between TFR and the individual determinants, it is evident that the individual region types are clearly associated with a different combination of socioeconomic determinants (Fig. 5 ). This is also evidenced by the one-way test ANOVA, which shows the presence of statistically significant differences between the region types and the socioeconomic indicators (Table 5 ). Thus, there are significant differences in TFR according to women's socioeconomic background.

Determinants of the spatial differentiation of fertility

In three separate multivariate analyses, the factor scores of both factors and TFR represented the dependent variables. A multiple linear regression (MLR) model was used to determine the joint effect of the nine socioeconomic determinants, using the Enter method to determine statistical significance with respect to the dependent variable. Before conducting the multivariate analysis, regression assumptions such as normality of residuals, homoscedasticity, multicollinearity, and independence of residuals were tested. The significance level for all tests was p < 0.05 and p < 0.001. The scientific interest was directed to the knowledge of primary predictors of Slovak regional fertility.

A linear relationship was initially assumed between each independent variable and Slovak regional fertility. The MLRs included only statistically significant effects of the chosen variables. The values of the R, R-squared, and Adjusted R-squared multiple correlation coefficients revealed a gradual decrease in model significance. However, the models retained high quality with high significant values, and ANOVA confirmed they all explain a substantial percentage of regional variation. Table 6 highlights that the variables included in the models can explain a significant 92 per cent ( p < 0.001) of the variance in fertility at fertility timing, a substantial 69 per cent ( p < 0.001) in fertility intensity, and a significant 68 per cent ( p < 0.001) in total fertility rate.

The prediction of the first factor value, which explains the difference in fertility timing in Slovakia's regions, was found to be statistically significant with only seven variables. Ethnicity and divorce rate did not affect the first factor and were excluded from multi-linear regression. However, multivariate analysis determined that low women's education, residential building, and women’s unemployment levels are significant predictors of fertility timing. The coefficients in Table 6 represent the effect of each independent variable on the dependent variable, which highlights that women’s low education significantly and positively affects the value of the fertility timing factor at p < 0.001. Increasing women's low education rate tended to increase the value of the given factor ( β = 0.348). The coefficient of unemployment ( β = 0.176) showed a significant ( p < 0.05) positive effect on the timing of fertility, i.e. at the fertility of younger women. Other variables had a negative effect on the model. The low intensity of residential building development significantly and negatively affects the timing factor's values, indicating fertility in older women ( β = −0.288). Similarly, the coefficients ( β = −0.173, β = −0.152, β = −0.151, β = −0.118) showed significant influence on the timing of older women's fertility at p < 0.05. These are the respective β coefficients for child kindergarten enrollment, income, urbanization, and Catholicism. This indicates that when the enrollment rate of children in kindergartens increases, the income increases, the rate of urbanization and Catholics also decreases, and the factor timing values decrease, which indicates the fertility of older women. These findings significantly impact our understanding of fertility patterns in Slovakia's regions.

The prediction of the value of the second factor, which clarifies the difference in fertility intensity in Slovakia's regions, was statistically significant, with only four variables at the 0.001 significant level. Five of the original variables were excluded from the model. The MLR revealed that Roma ethnicity, monthly income level, residential building, and the women's divorce rate significantly affect fertility intensity in the Slovak regions. Notably, increasing Roma ethnicity tended to increase the values of the given factor, i.e., fertility intensity ( β = 0.550). Similarly, fertility intensity in Slovakia's regions increases with monthly income or residential construction development ( β = 0.479, β = 0.388). The women's divorce rate indicator was negatively affected in the model. The lower rate of divorced women has a significant and negative effect on the values of the factor, indicating lower fertility intensity ( β = −0.533).

The final multivariate analysis was examined using the total fertility level, which also indicates the potential reproductive competence of the population. As a statistical measure, it estimates the average number of children a woman would bear in her lifetime if current age-specific fertility rates remain constant. It is a valuable tool for demographers and policymakers to understand and forecast population trends. The prediction of the level of TFR was statistically significant with five variables at the 0.001 and 0.05 levels, with Roma ethnicity ( β = 0.697) and residential building ( β = 0.302) indicating significant positive predictors of the level of TFR in the regions. Low levels of the above variables predict low levels of TFR. On the other hand, significant negative predictors of the level of TFR in the regions are unemployed women, enrollment of children in kindergartens, and divorced women in the region's population. If the values of the above variables increase ( β = −0.345, β = −0.306, β = −0.275), the level of TFR decreases.

The demographic transition and the related changes in people's reproductive behavior also affected the Slovak regions from the late 1990s (Mládek, 1999 ). The postponement of childbearing, the reduction of the marital birth rate, and the increase of one-child families and childless families due to the changed living, social, economic, and political conditions of the socialist model of reproductive behavior were the main reasons for the significant change in the fertility of the Slovak population with a decrease in the birth intensity and its stabilization far below the replacement rate (Šprocha & Tišliar, 2016 ). These findings are the driving force for the current research on fertility and natality under the conditions of Slovakia (Babinčák & Kačmárová, 2023 ; Bleha & Ďurček, 2019 ; Lentner & Horbulák, 2021 ; Šprocha & Fitalová, 2022 ; Šprocha & Tišliar, 2019 ; Šprocha et al., 2022 ). Moreover, the study's results highlight the main determinants of regional fertility in Slovakia, which are spatially significantly differentiated due to their nature and intensity.

The basic dimensions of Slovakia's regional fertility were developed through factor analysis, which provided a two-factor solution to the fertility assessment model. The two-factor model is supported by Šprocha et al’s ( 2022 ) independent research, but variations in input variables reverse the factors’ nature. The first factor indicates the nature of fertility, which differentiates regions in terms of the timing of fertility, and according to Šprocha and Šidlo ( 2016 ), the timing of fertility is the main factor in the variability of fertility in Slovakia. The second factor captures fertility intensity, which is influenced by demographic, socioeconomic, and cultural determinants, as well as the timing of fertility (Šprocha & Bačík, 2021a , 2021b ). To construct primary regional fertility types, a two-factor model of fertility was applied using selected socioeconomic determinants at two hierarchical levels. The cluster analysis generated almost homogeneous regional types of fertility nature and intensity. Regions A-F show low fertility levels, and G-J have higher fertility above the national average. The number of clusters is purposefully higher than those examined in Šprocha et al. ( 2022 ). This provides a more detailed investigation of regression analysis with selected determinants.

Research on the inter-regional fertility level confirmed the expected relations for the selected indicators, especially about its nature, which is less connected with its strength. Women's divorce rates show negative dependence, which is consistent with the findings of some studies (see Meggiolario & Ongaro, 2010 ; Van Bavel et al., 2012 ) that demonstrate divorce has a negative effect on human fertility. A low Slovak female divorce rate is, therefore, a guarantee of higher TFR values, as evidenced by regional types I and J. The study found a positive trend in the Catholic religion, in line with the findings and theoretical concepts of Philipov and Berghammer ( 2007 ) and Zhang ( 2008 ), albeit one that is less pronounced as the women's divorce rate, which is consistent with their findings and theoretical concepts. Catholics are among the religious groups that support marriage and children and oppose contraception and abortion, which would decrease their fertility. Their less pronounced dependence confirms Šprocha and Tišliar's ( 2019 ) claim about losing the power of religiosity as a differential factor in reproductive behavior in Slovakia. However, it is still true that Slovak regions with a low concentration of Catholics achieve low TFR. The high and positive dependency on TFR among Roma ethnicity is related to their significantly different reproductive behavior (Nestorová Dická, 2021 ), which manifests itself in higher fertility intensity, especially in a socially excluded environment (Šprocha, 2014 ). Areas of higher concentration of the Roma population also guarantee a higher level of TFR. As in this study, Roma ethnicity was a significant predictor of fertility by Šprocha and Bleha ( 2018 ). Educating women plays a significant role in the final level of fertility, particularly in influencing the TFR. Research indicates that women's low education is directly linked to higher TFR, as lower educational attainment often correlates with earlier and more frequent childbearing (cf. Šprocha et al., 2020 ). Our analysis confirms this, showing a statistically significant relationship between lower educational levels and higher TFR across Slovak regions.

At the same time, socioeconomic controls revealed the connection of the Roma community with a low level of education, women's employment, and income, which was also pointed out by Rosičová et al. ( 2009 ), Preoteasa ( 2013 ), Andrei et al. ( 2014 ), etc. Similarly, urbanization, documenting the advancement of human civilization with social and economic progress, is more closely related to higher education (Marginson, 2016 ) and divorce rate (Zhang et al., 2014 ) than rural areas, as well as higher economic potential, which is documented by higher incomes or GDP (Henderson, 2003 ; Sancar & Sancar, 2017 ). Research indicates that economically developed regions are directly related to a lower TFR, as a higher level of education of women often correlates with later and less childbearing (cf. Šprocha et al., 2020 ). Several studies have also confirmed the relationship between religion, including Catholicism, and the divorce rate (e.g., Corley & Woods, 2021 ; Sander, 2019 ) and the availability of childcare facilities and unemployment for women and men (Kim, 2018 ; Legazpe & Davia, 2019 ).

Similarly, women's unemployment had a positive dependence. This is explained by Becker's neoclassical theory, which states that unemployment should reduce the cost of lost opportunities by providing time for childbearing and child care, thus promoting human fertility (Cazzola et al., 2016 ). Urbanisation exhibited a negative trend in fertility outcomes, which can be explained by the compositional or context hypothesis (see more Kulu, 2013 ; Kulu & Washbrook, 2014 ). Riederer and Buber-Ennser ( 2019 ) add that the main reason for the postponement of births in urban regions, where actual fertility rates are lower, in Eastern European countries may be precisely the difference in the context of the urban-suburban-rural gradient. Although monthly income shows a negative influence, it has a less pronounced tightness, which agrees with the earlier findings of Marenčáková ( 2006 ), who also confirmed the negative relationship between income and fertility in Slovakia.

The kindergarten enrolment rate has a significantly negative fertility impact in regions where the total fertility rate decreases as the enrolment rate increases. There are contrasting reports of childcare's influence on fertility. Some researchers consider a positive effect of available childcare but add that the results of several empirical studies do not support the hypothetical expectations (Wood & Neels, 2019 ; Ridfuss et al., 2010 ). Our research confirmed this, but the relationship may be related to many children from a socially disadvantaged environment without pre-primary education. However, Varsik ( 2019 ) considers that children from marginalized Roma communities have low enrolment rates, which conditions its negative effect on their communities. These communities are more concentrated in regional types with a higher level of fertility.

Only residential building demonstrated independence, but findings vary. Some confirm the causal relationship between housing affordability as the independent variable and fertility behavior as the dependent variable, often observed in less developed societies where the state controls the housing market (Felson & Solaún, 1975 ). Kostelecký and Vobecká ( 2009 ) found the existence of specific connections in Czechia when the improvement of the economic situation (increase in GDP and housing construction, decrease in inflation and unemployment) was accompanied by an improvement in the availability of owner-occupied housing and an increase in the birth rate. While the importance of housing availability has been scientifically proven, Salvati ( 2021 ) recorded that the positive impact of residential building was confirmed only in the initial phase of urban development. Considering the observed independence at the inter-regional level and the prevailing positive dependence at the intra-regional level, research in this direction requires further investigation into other housing factors that significantly impact fertility outcomes. For example, affordability (Clark et al., 2020 ) may significantly impact actual birth rates and TFR more than the development of new residential buildings.

However, the current nature and strength of the relationship between selected socioeconomic determinants and TFR are not identical within the individual types at the intraregional and interregional levels. From the assessment of the impact of TFR, it follows that individual regional types have different associations with the determinants studied, which was also confirmed by a one-way ANOVA test with statistically significant differences between regional types and socioeconomic determinants. Thus, the research demonstrated significant differences in TFR depending on the socioeconomic background of women, which was also confirmed in the study of Polykretis and Alexakis ( 2021 ).

The two MLR analyses determined that urbanisation, Catholicism, and women’s low level of education do not influence fertility level or intensity. However, these variables significantly affect fertility timing and differentiate younger and older women’s fertility, while the variable of Roma ethnicity is not statistically significant, which contradicts other analyses. In Slovak regions, fertility timing is not only associated with Roma issues but also in some "non-Roma" regions, fertility of younger women is significant, especially in the south of Slovakia (Levice, Poltár, Veľký Krtíš, Krupina districts), where fertility timing is also associated with the increase in out-of-wedlock births (Šprocha & Tišliar, 2021 ), which was predicted for both Hungarian and Roma populations. In addition, Roma ethnicity is a significant predictor of fertility intensity and level in Slovak regions. This is supported by the results of the studies, e.g. Šprocha et al. ( 2022 ), Nestorová Dická ( 2021 ), Szabó et al., 2021 , Šprocha, ( 2014 ), Potančoková et al. ( 2008 ), which point to the higher reproductive characteristics of Roma population in Slovak regions. Šprocha and Bleha ( 2018 ) add that at least two-thirds of the overall variability is explained by some selected "socioeconomic" indicators and the share of the Roma population.

In the initial phase of the research, it was established that variations in fertility and birth rates are predominantly stratified along the urban–rural continuum. Notably, rural areas in Slovakia exhibit significantly higher fertility rates. However, as Nestorová Dická et al. ( 2019 ) highlighted, extreme rural municipalities characterized by low population density experience notably diminished population reproduction rates. Consequently, it becomes evident that fertility within Slovak rural areas primarily thrives within suburban municipalities and those with moderate population sizes. Nevertheless, two multiple linear regression (MLR) models indicate that the urban–rural gradient exerts negligible influence on the intensity and magnitude of fertility outcomes within the Slovak interregional framework, a finding corroborated by Šprocha et al.'s ( 2022 ) study in Slovakia. The distribution of the populace across urban and rural settings finds validation in fertility timing, as underscored by the research conducted by Riederer and Buber-Ennser ( 2019 ).

Unemployment has also become an important positive predictor of fertility timing, but it has a negative effect on the total fertility rate. Slovak economically developed regions (Korec, 2009 ) achieve higher fertility levels with high employment (Šprocha & Bleha, 2018 ) due to selective migration (Novotný et al., 2023 ), but also housing availability. On the other hand, Šprocha et al. ( 2022 ) supplement that young people in this area face problems related to high housing prices and low childcare substitutability rate (Križan et al., 2022 ; Madajová et al., 2021 ) due to insufficient capacity. Consistent with these conditions, an important finding of Mills et al. ( 2011 ) is that educated people are more likely to focus on building a career and, therefore, seek to combine parenthood at an older age, which affects their fertility outcomes, confirmed by the results of the first MLR.

The most important determinant affecting regional fertility differences is women's education, especially young women's education, according to research by Kostelecký and Vobecká ( 2009 ). The authors add that when women's education is controlled, housing affordability plays an important role in explaining regional differences in fertility—both the total fertility rate and the fertility timing. However, women’s low education was not significantly related to the level or intensity of fertility outcomes in Slovak regions. Götmark and Andersson ( 2020 ) support this finding in Eastern European countries, where there was no or a weak relation between education and fertility outcomes.

Slovakia's reproductive potential seems to have been stabilised for a long time below the level of insufficient population replacement. Therefore, research into understanding and predicting total and regional fertility with the prediction of further development is important for various scientific disciplines and interest groups.

Each determinant influencing fertility has specific spatial patterns with unequal regression coefficients at different regional levels, which cannot be summarised in a constant way. Therefore, implementing multivariate statistical techniques can adequately describe the relationships between fertility and its determinants. Mathematical-statistical techniques can potentially contribute to demography, geography, and social sciences by offering usually invisible solutions, enabling practitioners to better understand relationships' spatial perspectives. In this context, the study was to reveal the effect of a set of nine socioeconomic determinants on the level of regional fertility. To achieve this, spatial changes in the distribution of fertility and determinants were captured, and spatial heterogeneity in their relationships was examined using regression techniques.

We analyzed fertility variations across Slovak regions, examining the convergence or divergence of our regional findings about widely accepted theories on the determinants influencing fertility levels. The results highlighted that selected socioeconomic determinants were not unnecessary in any case, and they all showed certain regional connections about fertility nature and level. We have demonstrated that regional variations in fertility rates arise from economic, social, and cultural factors. The models differ regarding the nature and intensity of fertility in relation to the urban–rural dichotomy, the educational or Roma issue. The persistence of geographic variation will be important for understanding Slovak regional fertility levels.

Knowledge of prevailing geographic and population influences is essential to understanding Slovakia's regional fertility levels and intensity. Given that fertility is vital for social assessment and policy formulation, the study's findings could help local decision-makers and planners identify the socioeconomic conditions underlying fertility at the regional level and plan appropriate intervention strategies.

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Acknowledgements

The authors would like to thank the reviewers for their comments, suggestions, and notes, which significantly helped improve the paper's original version.

Open access funding provided by The Ministry of Education, Science, Research and Sport of the Slovak Republic in cooperation with Centre for Scientific and Technical Information of the Slovak Republic. This research was supported by the Scientific Grant Agency of the Ministry of Education, science, research and sport of the Slovak Republic and the Slovak Academy of Sciences. Grant Number VEGA 1/0514/21 “Spatial redistribution of human capital as an indicator of the formation of the regional system in Slovakia”. Grant Number VEGA 1/0768/24 Multiscale assessment of spatial variability of social-economic population stratification.

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Research on the renewal of multi-story high-density urban landscape based on property rights land—a case study of the self-built liu houses in zherong, fujian province, 1. introduction, 2. materials and methods, 3. results: case study—zherong county, fujian province.

② History of the County
(ii) Regional Morphological Feature: Lack of Certain Regularity
(iii) Architectural Feature: Significant Diversity Exists
(iv) Summary of Early Liu House Features
② Sample B: Mid-term Liu Houses (i) Morphology and Structure of Land Parcels
(ii) Regional Morphological Feature: Pattern with Certain Regularity
(iii) Architectural Feature: Balanced Similarity and Diversity
(iv) Summary of Mid-Term Liu House Features
③ Sample C: Late Liu Houses (i) Morphology and Structure of Land Parcels
(ii) Regional Morphological Feature: Strong Regularity
(iii) Architectural Features: Highly Unified Similarity
(iv) Summary of Late Liu House Features
② Estimation-Based Renovation Framework of Liu House Areas in Zherong

4. Discussion

(ii) Individual Construction Driven by the Residents
② Mid-term Liu Houses: Morphological and Architectural Features Affected by both the Government and the Residents (i) Land Parcels Shaped by Administrative Planning
(ii) Collective Construction Driven by Spontaneously Formed Resident Groups
③ Late Liu Houses: Unified Morphological and Architectural Features Under Developers’ Direct Control (i) Commercial Real Estate Development
(ii) Unified Construction Led by Commercial Developers

5. Conclusions

Author contributions, data availability statement, conflicts of interest.

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Click here to enlarge figure

Content	Sub-Content	Detailed Content	Indicators	Weight Values
Building scale	Heights	Average floor height	The average floor height of the target building is added or subtracted from the average of the block and block in which the building is located, and the difference is recorded as H1 and H2, respectively.	In the calculation, the weight values k1 and k2 are used, respectively.
	Heights	Number of floors	Add or subtract from the average of the blocks and blocks, and the difference is recorded as H1 and H2.	In the calculation, the weight values K1 and K2 are used, respectively.
	Volume	Width	Add or subtract from the average of the blocks and blocks, and the difference is recorded as w1 and w2.	In the calculation, the weight values q1 and q2 are used, respectively.
		Length	Add or subtract from the average of the blocks and blocks, and the difference is recorded as d1 and d2.	In the calculation, the weight values q3 and q4 are used, respectively.
		Area	Add or subtract from the average of the blocks and blocks, and the difference is recorded as a1 and a2.	In the calculation, the weight values q5 and q6 are used, respectively.
	Concave and convex	If courtyard	Bool value is ɑ1.	The weight value x1 is used in the calculation.
		If terrace	Bool value is ɑ2.	The weight value x2 is used in the calculation.
		If Bay window	Bool value is ɑ3.	The weight value x3 is used in the calculation.
		If concave and convex over 50 cm	Bool value is ɑ4.	The weight value x4 is used in the calculation.
Plan elements	Building setback	Building setback scales	Bool value is ɑ5.	The weight value y1 is used in the calculation.
Facade elements	Roof form	If similar	Bool value is ɑ6.	The weight value u1 is used in the calculation.
	Mian form	If similar	Bool value is ɑ7.	The weight value u2 is used in the calculation.
	Base form	If similar	Bool value is ɑ8.	The weight value u3 is used in the calculation.
	Color	If similar	Bool value is ɑ9.	The weight value u4 is used in the calculation.
	Material	If similar	Bool value is ɑ10.	The weight value u5 is used in the calculation
	Ornament	If similar	Bool value is ɑ11.	The weight value u6 is used in the calculation,

Types of Liu Houses	Time	Architectural Features
Early Liu House	1980–1990	(1) The number of floors is no less than 3 and no more than 6 floors. (2) The pediments of the townhouses are independent of each other, and the construction is led by the residents.
Mid-term Liu House	1990–1995	(1) The number of floors is no less than 3 and no more than 6 floors. (3) Townhouse buildings share common pediments.
Late Liu House	1995+	(1) The number of floors is no less than 3 and no more than 6 floors. (2) Townhouse buildings share common walls and foundations and are constructed by the developer in a unified manner.

Content	Sub-Content	Detailed Content	Difficulty of Renovation Construction	Weight Values
Building scale	Heights	Average floor height	High	Considering the difficulty of the update construction, k1 = k2 = 10
	Heights	Number of floors	High	Considering the difficulty of the update construction, K1 = K2 = 10
	Volume	Width	Very high	Considering the difficulty of the update construction, q1 = q2 = 20
		Length		Considering the difficulty of the update construction, q3 = q4 = 20
		Area		Considering the difficulty of the update construction, q5 = q6 = 20
	Concave and convex	If courtyard	High	x1 = 10 is set to take into account the difficulty of updating the construction
		If terrace		x1 = 10 is set to take into account the difficulty of updating the construction
		If Bay window		x1 = 10 is set to take into account the difficulty of updating the construction
		If concave and convex over 50 cm		x1 = 10 is set to take into account the difficulty of updating the construction
Plan elements	Building setback	Building setback scales	Very high	y1 = 20 is set to take into account the difficulty of updating the construction
Facade elements	Roof form	If similar	Medium	u1 = 2 is set to take into account the difficulty of updating the construction
	Mian form	If similar	Medium	u2 = 2 is set to take into account the difficulty of updating the construction
	Base form	If similar	Low	u3 = 1 is set to take into account the difficulty of updating the construction
	Color	If similar	Low	u4 = 1 is set to take into account the difficulty of updating the construction
	Material	If similar	Medium	u5 = 2 is set to take into account the difficulty of updating the construction
	Ornament	If similar	Low	u6 = 1 is set to take into account the difficulty of updating the construction

Control Level	Control Target	Range of Number X	Control Methods
Level 1	The diversity of form is high	>180	not much guidance required
Level 2	Diversity is comparatively high	100–180	Certain guidance required
Level 3	Diversity is normal	50–100	Constraints and control needed
Level 4	Diversity is comparatively low	20–50	Strict constraints and control needed
Level 5	Diversity is very low	<20	An overall renovation may be more suitable

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Li, N.; Cao, Z.; Wang, K. Research on the Renewal of Multi-Story High-Density Urban Landscape Based on Property Rights Land—A Case Study of the Self-Built Liu Houses in Zherong, Fujian Province. Buildings 2024 , 14 , 1998. https://doi.org/10.3390/buildings14071998

Li N, Cao Z, Wang K. Research on the Renewal of Multi-Story High-Density Urban Landscape Based on Property Rights Land—A Case Study of the Self-Built Liu Houses in Zherong, Fujian Province. Buildings . 2024; 14(7):1998. https://doi.org/10.3390/buildings14071998

Li, Ningyuan, Zhenyu Cao, and Ka Wang. 2024. "Research on the Renewal of Multi-Story High-Density Urban Landscape Based on Property Rights Land—A Case Study of the Self-Built Liu Houses in Zherong, Fujian Province" Buildings 14, no. 7: 1998. https://doi.org/10.3390/buildings14071998

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1.2 Defining Research Methodology. It is an essential process of any scientific study, which serves as a framework for processing and achieving the predicted outcomes of the study. It is commonly defined as a systematic and organized process of collecting, analyzing, interpreting, and presenting information to answer specific questions or solve ...
Social Science Research: Principles, Methods and Practices
The text provides a basic introduction to research methods in the social sciences. Updates in social science inquiry with respect to social media and popular culture platforms and mixed methods research should be easy to incorporate. Clarity rating: 5 The text has been written from the point of view of a non-expert.
Introduction to Research Methods: A Hands-on Approach
The Second Edition of Introduction to Research Methods: A Hands-on Approach by Bora Pajo continues to make research easy to understand and easy to construct. Covering both quantitative and qualitative methods, this new edition lays out the differences between research approaches so readers can better understand when and how to use each research ...
(PDF) Introduction to research: Mastering the basics
Accepted February 25, 2023. This paper provides an in-depth introduction to r esearch methods. and discusses numerous aspects r elated to the r esearch process. It. begins with an overview of ...
5.1: Introduction to Research Methods Definitions and Roles
Introduction to Research Methods. In academic pursuits, mastering research methods is an indispensable skill. This chapter aims to equip you with a comprehensive understanding of research methodologies through the lens of critical thinking, reading, and writing. Whether you're preparing for a research paper, thesis, or just aiming to enhance ...
Writing a Research Paper Introduction
Table of contents. Step 1: Introduce your topic. Step 2: Describe the background. Step 3: Establish your research problem. Step 4: Specify your objective (s) Step 5: Map out your paper. Research paper introduction examples. Frequently asked questions about the research paper introduction.
Introduction to Research Methods
Introduction. A research method is a set of procedures for collecting and analyzing data during research. This guided tutorial outlines the three kinds of research methods and gives examples of when and how to use them. This tutorial is hosted through LibWizard.
Introduction to Research Methods : A Hands-On Approach
With clear, engaging, and humorous prose, Introduction to Research Methods: A Hands-on Approach offers readers an applied introduction to the exciting world of social science research. Using real, annotated research examples, the text invites readers to see research as a dynamic conversation on timely topics that are relevant to their lives.
PDF Introduction to Research Methods
Introduction to . Research Methods. A. s a psychologist, the entire framework behind learning about psychology is being able to study human behavior. Not everyone will ultimately conduct research for a career, but in order to understand human behavior, we must have an appreciation for the research
Introduction to Research Methods
A comprehensive introductory research methods guide, this textbook provides students with an understanding of the concepts and techniques of qualitative and quantitative research. It uses simple examples and practice exercises to demystify complex theories and methodologies. Features include: · STQ's - Self Testing Questions (and answers) · Summaries, suggestions for further reading ...
Introduction to Research Methods: A Hands-On Approach
The SAGE edge site for Introduction to Research Methods by Bora Pajo offers a robust online environment you can access anytime, anywhere, and features an impressive array of free tools and resources to keep you on the cutting edge of your learning experience. Introduction to Research Methods: A Hands-On Approach makes learning research methods ...
(PDF) Introduction to Research Methods
In simple terms it is method of. observation that is gather through non-numerical data. The type of research. includes various methods of collecting data through case studies, interviews, focus ...
Introduction to research methods : a practical guide for anyone
"Introduction to Research Methods: A Practical Guide for Anyone Undertaking a Research Project" by Catherine Dawson is an invaluable resource for students and researchers alike. Dawson provides a comprehensive and accessible guide, making the often daunting task of undertaking a research project more manageable especially if you have https ...
Introduction to Research Methods
Research Methods for the Social Sciences (Pelz) This text will introduce you to the fascinating and important study of the methods of inquiry in the Social Sciences. You will learn both the logic behind - and the procedures for - a wide variety of research methods, including correlational and experimental designs.
Introduction to Research Methods
This book encompasses 1) the development of a research project and 2) the analysis of the resulting data you might collect. The first half of the book concentrates on the development of a research project. That half of the book is written for a student that has to write a class research paper or thesis and doesn't know where to start.
Regional fertility predictors based on socioeconomic determinants in
The study's primary purpose was to recognise the effects of determinants on the level of fertility and thereby explain the differences in trends in the regions of Slovakia. At the turn of the century, the differences in fertility in regions increased, but the total fertility rate decreased. Multivariate statistical methods clarified the regional effects of the level and nature of fertility ...
A mixed‐methods study of the quality of parental support during
Introduction In Europe, most Internet searches for school‐related tasks are situated at home, where parents can support adolescents. Although the frequency (quantity) of parental support has already been analyzed, a research gap exists concerning the quality of parental support in adolescents' information‐related Internet use. The quality of parental support in the field of homework ...
(PDF) Introduction to Research methods
The purpose of "Introduction to Research Methods" is to provide readers with a comprehensive and accessible overview of the fundamental principles, techniques, and practices involved in conducting ...
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Unlike in Western countries, land ownership in China is overwhelmingly vested in the state, and individuals cannot directly own private lands and build houses. Therefore, developers will contract the land to the government and build it into collective apartments. Against this backdrop, a different kind of multi-story, high-density self-built residential buildings is widespread in small towns ...
TAAC: Secure and Efficient Time‐Attribute‐Based Access Control Scheme
1. Introduction. Software-defined networking (SDN) is an innovative network construction technology. Compared to traditional network architectures [] that require tedious manual configuration for management and optimization, SDN technology separates the network's control plane from its data plane, allowing for programable, flexible configuration and management [] through a centralized ...

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Research Methods | Definition, Types, Examples

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Introduction to Research Methods

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Regional fertility predictors based on socioeconomic determinants in Slovakia

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