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Page 1 of 2

The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
  • The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
  • Volume 1: Building a Program of Research
  • Edited by Austin Lee Nichols, John Edlund
  • Coming soon
  • Expected online publication date: March 2023
  • Print publication: 31 March 2023
  • View description
    The first of three volumes, the five sections of this book cover a variety of issues important in developing, designing, and analyzing data to produce high-quality research efforts and cultivate a productive research career. First, leading scholars from around the world provide a step-by-step guide to doing research in the social and behavioral sciences. After discussing some of the basics, the various authors next focus on the important building blocks of any study. In section three, various types of quantitative and qualitative research designs are discussed, and advice is provided regarding best practices of each. The volume then provides an introduction to a variety of important and cutting-edge statistical analyses. In the last section of the volume, nine chapters provide information related to what it takes to have a long and successful research career. Throughout the book, example and real-world research efforts from dozens of different disciplines are discussed.
  • 16 - Sex Differences and Sex Similarities
  • from Part II - Middle-Level Theories
  • Edited by Todd K. Shackelford, Oakland University, Michigan
  • Book: The Cambridge Handbook of Evolutionary Perspectives on Sexual Psychology
  • Published online: 30 June 2022
  • Print publication: 21 July 2022, pp 360-389
  • View extract

    Summary

    The sciences have been perennially interested in understanding similarities and differences between the sexes. Among humans, both males and females seek to secure serially monogamous partnerships with kind and intelligent mates similar to themselves. However, the sexes differ in the relative value placed on resources and physical attractiveness, their willingness to engage in short-term liaisons, and jealousy in response to emotional and sexual infidelities. Consideration of cultural factors, modern relationship innovations, and diversity in sexual orientation and gender identity provides further complexity to our understanding of similarities and differences. Recommendations are made for future research in these areas, and the societal implications of evolutionary work on the sexes is discussed.

  • 19 - Development and Applications of Item Response Theory
  • from Part Five - New Statistical Trends in the Social and Behavioral Sciences
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 309-327
  • View extract

    Summary

    Item response theory (IRT) represents an alternative measurement approach to Classical test theory (CTT) that has been developed to address some of the key limitations in CTT. IRT utilizes a logistic function to jointly scale both person characteristics (e.g. ability) and task characteristics (e.g. difficulty) along a common metric, and is grounded upon the notion that different item sets should not result in different scaling solutions. This provides IRT with a number of advantages over CTT; namely that the performances of individuals who are administered different sets of tasks may still be justifiably compared. From this basis, the IRT approach has established its utility through its applications in such varied contexts as adaptive testing, cognitive diagnostic modeling, item difficulty modeling, and latent class analyses. The current chapter focuses on applied issues in measurement with IRT, with emphasis on its distinct advantages over traditional approaches.
  • 2 - Reliability and Validity of Measurement in the Social and Behavioral Sciences
  • from Part One - Performing Good Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 21-37
  • View extract

    Summary

    In this chapter, the authors review concepts related to reliability and validity of measurement in the social sciences. Necessarily eschewing detailed reviews of statistical methods to examine reliability and validity of measurement, the authors focus on terse discussion on key concepts and elementary methods. In addition, given the immense literatures on topics the authors could only discuss in brief, the authors point to sources that provide helpful, focused treatments of undiscussed ideas and techniques. Authors conclude that, given reliability and validity of measurement is crucial to perform scientific research, social scientists ought to prioritize establishing evidence for reliability/validity of measurement for social scientists’ measures and experimental methods.
  • 17 - Cross-Cultural Research
  • from Part Four - Emerging Issues in Social and Behavioral Science Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 274-286
  • View extract

    Summary

    The chapter begins with a description of the historical roots of comparative research, followed by a description of its spectacular in the last 50 years. The core methodological issues of the field are described: Does an instrument that is administered in different groups or countries constitute and adequate measure of the underlying construct in each application? If so, can we compare scores across groups and countries. A taxonomy of equivalence (similarity of meaning) and bias (presence of nuisance factors) to be considered in comparative studies is described. Special emphasis is given to test adaptations a tool to provide culture-informed measures. The gap between the advanced statistical procedures available to analyze comparative data and the much less advanced level of our theories of cross-cultural similarities and differences is mentioned as a key challenge for the future.
  • 5 - Using the Internet for Research
  • from Part One - Performing Good Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 68-82
  • View extract

    Summary

    The Internet was created in the mid-20th century as a communication tool for American scientists. Since then, it has grown into a tool that much of the world’s population uses on a daily basis for a wide variety of reasons ranging from social interaction, commerce, and to obtain information. Given its ubiquity, the amount of scholarship on the use of the Internet for conducting research has grown along with it. To date, thousands of books and journal articles include research conducted on the Internet using myriad research methodologies and theoretical perspectives. This chapter reviews the literature on Internet research, exploring questions such as: What is Internet research? What topics do social scientists study on the Internet? What are the different approaches for conducting research on the Internet? Ethical considerations for Internet research, suggestions for best practices in using the Internet for research, and recommendations for future research conclude this chapter.
  • 18 - A Gentle Introduction to Bayesian Statistics
  • from Part Five - New Statistical Trends in the Social and Behavioral Sciences
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 289-308
  • View extract

    Summary

    Bayesian methods are becoming more popular in the social sciences because they offer solutions to problems that arise with classical methods, e.g., convergence issues and the inability to interpret the results probabilistically. However, Bayesian statistics remain controversial because they require specifying prior distributions that reflect the researcher’s state of knowledge before observing the data. Critics of Bayesian statistics note that prior distributions allow researchers to sway the results in the desired direction. This chapter shows how to conduct a Bayesian mediation analysis using real data from a study of delays in PhD completion in the Netherlands. The authors illustrate the challenges in specifying prior distributions and how to examine the influence of a prior distribution in a sensitivity analysis. The chapter also contains detailed examples of how to report the results of a Bayesian mediation analysis and future directions for the field of applied statistics for social sciences.
  • 3 - Performing Research in the Laboratory
  • from Part One - Performing Good Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 38-52
  • View extract

    Summary

    The current chapter attempts to cover the most important aspects of conducting research in the laboratory while allowing the reader to refer to other chapters in this volume to better understand the most prevalent and important limitations of the lab. We begin by describing what a lab is and by giving examples, from our own research and others, of the many different ways that a normal space can be used for laboratory research. We then explore the many advantages and disadvantages that often result from lab research, followed by the different types of research that are often conducted in the lab. Next, we move on the some of the many issues that one must consider when conducting lab research. We focus this section on issues related to both participants and potential research assistants, including recruitment, training, and minimizing biases. Following this, we present the different types and uses of deception while encouraging the reader to carefully examine each research question and study design before making any research decision. Finally, we discuss the generalizability of lab research to the real world and provide some considerations for increasing the likelihood that your research will generalize.
  • 16 - Interdisciplinary Research
  • from Part Four - Emerging Issues in Social and Behavioral Science Research
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 258-273
  • View extract

    Summary

    Interdisciplinary research (IDR) focuses on particular problems or questions that are too comprehensive to be answered satisfactorily by any one discipline. Overall, across disciplines, the practice of IDR is rapidly accelerating because the combination of researchers from different disciplines allows complicated problems to be solved. There is an urgent need for IDR and specific interdisciplinary training to address pressing social, political, economic challenges society faces. Additionally, the necessity to prepare students for an increasingly interdisciplinary, collaborative, and global future also calls for interdisciplinary exposure in post-secondary education. In this article, we aim to provide an explanation of IDR, and to offer a guiding framework towards interdisciplinary research with measurable and positive impact.
  • 10 - Physiological Measures
  • from Part Three - The Social and Behavioral Scientist’s Toolkit
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 147-167
  • View extract

    Summary

    Many studies in behavioral science involve physiological measures because they allow the researcher a window into some underlying neural and biological processes. The use of such measures requires a multiple-levels-of-analysis approach to understanding behavior, where the physiological processes are just one level of analysis that should be considered in conjunction with others, such as the social situation or the structure of society. We provide an overview of three basic principles of psychophysiology that are important to consider when planning and interpreting research with these measures. We then give a brief introduction to most commonly used measures, including those that tap into in the autonomic nervous system (e.g., electrodermal activity, heart rate), hormones (e.g., cortisol, testosterone), muscle activity (e.g., facial electromyography), and the brain (e.g., event-related potentials, functional brain imaging). The chapter concludes with tips for reducing participant anxiety during experiments, which can otherwise interfere with physiological recordings.
  • 20 - Social Network Analysis
  • from Part Five - New Statistical Trends in the Social and Behavioral Sciences
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 328-345
  • View extract

    Summary

    This chapter provides an introduction to Social Network Analysis (SNA) for social scientists that are new to the method. As a theoretical perspective and a research method, SNA distinguishes itself from other research methods by focusing on social relationships and the idea that social actors (e.g., individuals, groups, organizations, and countries) are influenced by the patterns of social relations surrounding them. SNA enables researchers to investigate these patterns and understand their antecedents and consequences. In this chapter, we articulate the logic of key network concepts and provide a visual roadmap that helps researchers in navigating through measures and methods and at different levels of analysis. Extensive references to further readings, empirical applications, and methodological contributions are given.
  • 11 - Eyetracking Research
  • from Part Three - The Social and Behavioral Scientist’s Toolkit
  • Edited by John E. Edlund, Rochester Institute of Technology, New York, Austin Lee Nichols
  • Book: Advanced Research Methods for the Social and Behavioral Sciences
  • Published online: 22 February 2019
  • Print publication: 14 March 2019, pp 168-190
  • View extract

    Summary

    Despite our conscious experience, the image quality (and information density) of the human visual system varies dramatically across the visual field. Only a small, central fovea (covering less than 0.01% of the visual field) provides enough acuity to support common tasks like reading. The oculomotor system overcomes this limitation by rapidly rotating the eyes to foveate objects of interest with saccades and stabilizes those objects with a range of other eye movements. Critically, humans usually foveate objects that they attend to, even if those objects do not require high acuity, so an observer’s point of gaze offers an externally observable marker of attention. Chapter 11 describes the oculomotor system, a taxonomy of eye-movement types, the different types of eyetracking instrumentation available to monitor gaze in the laboratory and in natural environments, data quality issues in eyetracking, and introduces several sample applications in the social sciences.

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