Morling b 2012 research methods in psychology

Beth Morling - Research Methods in Psychology_ Evaluating a World of Information.pdf
THIRD EDITION

Research Methods in Psychology EVALUATING A WORLD OF INFORMATION

THIRD EDITION

Research Methods in Psychology EVALUATING A WORLD OF INFORMATION

Beth Morling UNIVERSITY OF DELAWARE

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Library of Congress Cataloging-in-Publication Data

Names: Morling, Beth, author. Title: Research methods in psychology : evaluating a world of information / Beth Morling, University of Delaware. Description: Third Edition. | New York : W. W. Norton & Company, [2017] | Revised edition of the author’s Research methods in psychology, [2015] | Includes bibliographical references and index. Identifiers: LCCN 2017030401 | ISBN 9780393617542 (pbk.) Subjects: LCSH: Psychology—Research—Methodology—Textbooks. | Psychology, Experimental—Textbooks. Classification: LCC BF76.5 .M667 2017 | DDC 150.72—dc23 LC record available at https://lccn.loc.gov/2017030401

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For my parents

vii

Brief Contents

PART I Introduction to Scientific Reasoning CHAPTER 1 Psychology Is a Way of Thinking 5

CHAPTER 2 Sources of Information: Why Research Is Best and How to Find It 25

CHAPTER 3 Three Claims, Four Validities: Interrogation Tools for Consumers of Research 57

PART II Research Foundations for Any Claim CHAPTER 4 Ethical Guidelines for Psychology Research 89

CHAPTER 5 Identifying Good Measurement 117

PART III Tools for Evaluating Frequency Claims CHAPTER 6 Surveys and Observations: Describing What People Do 153

CHAPTER 7 Sampling: Estimating the Frequency of Behaviors and Beliefs 179

PART IV Tools for Evaluating Association Claims CHAPTER 8 Bivariate Correlational Research 203

CHAPTER 9 Multivariate Correlational Research 237

PART V Tools for Evaluating Causal Claims CHAPTER 10 Introduction to Simple Experiments 273

CHAPTER 11 More on Experiments: Confounding and Obscuring Variables 311

CHAPTER 12 Experiments with More Than One Independent Variable 351

PART VI Balancing Research Priorities CHAPTER 13 Quasi-Experiments and Small-N Designs 389

CHAPTER 14 Replication, Generalization, and the Real World 425

Statistics Review Descriptive Statistics 457

Statistics Review Inferential Statistics 479

Presenting Results APA-Style Reports and Conference Posters 505

Appendix A Random Numbers and How to Use Them 545

Appendix B Statistical Tables 551

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BETH MORLING is Professor of Psychology at the University of Delaware. She attended Carleton College in Northfield, Minnesota, and received her Ph.D. from the University of Massachusetts at Amherst. Before coming to Delaware, she held positions at Union College (New York) and Muhlenberg College (Pennsylvania). In addition to teaching research methods at Delaware almost every semester, she also teaches undergraduate cultural psychology, a seminar on the self- concept, and a graduate course in the teaching of psychology. Her research in the area of cultural psychology explores how cultural practices shape people’s motivations. Dr. Morling has been a Fulbright scholar in Kyoto, Japan, and was the Delaware State Professor of the Year (2014), an award from the Council for Advancement and Support of Education (CASE) and the Carnegie Foundation for the Advancement of Teaching.

About the Author

ix

Preface

Students in the psychology major plan to pursue a tremendous variety of careers— not just becoming psychology researchers. So they sometimes ask: Why do we need to study research methods when we want to be therapists, social workers, teachers, lawyers, or physicians? Indeed, many students anticipate that research methods will be “dry,” “boring,” and irrelevant to their future goals. This book was written with these very students in mind—students who are taking their first course in research methods (usually sophomores) and who plan to pursue a wide variety of careers. Most of the students who take the course will never become researchers themselves, but they can learn to systematically navigate the research information they will encounter in empirical journal articles as well as in online magazines, print sources, blogs, and tweets.

I used to tell students that by conducting their own research, they would be able to read and apply research later, in their chosen careers. But the literature on learning transfer leads me to believe that the skills involved in designing one’s own studies will not easily transfer to understanding and critically assessing studies done by others. If we want students to assess how well a study supports its claims, we have to teach them to assess research. That is the approach this book takes.

Students Can Develop Research Consumer Skills To be a systematic consumer of research, students need to know what to priori- tize when assessing a study. Sometimes random samples matter, and sometimes they do not. Sometimes we ask about random assignment and confounds, and sometimes we do not. Students benefit from having a set of systematic steps to help them prioritize their questioning when they interrogate quantitative infor- mation. To provide that, this book presents a framework of three claims and four validities, introduced in Chapter 3. One axis of the framework is the three kinds of claims researchers (as well as journalists, bloggers, and commentators) might make: frequency claims (some percentage of people do X), association claims (X is associated with Y), and causal claims (X changes Y). The second axis of

x PREfACE

the framework is the four validities that are generally agreed upon by methodol- ogists: internal, external, construct, and statistical.

The three claims, four validities framework provides a scaffold that is rein- forced throughout. The book shows how almost every term, technique, and piece of information fits into the basic framework.

The framework also helps students set priorities when evaluating a study. Good quantitative reasoners prioritize different validity questions depending on the claim. For example, for a frequency claim, we should ask about measurement (construct validity) and sampling techniques (external validity), but not about ran- dom assignment or confounds, because the claim is not a causal one. For a causal claim, we prioritize internal validity and construct validity, but external validity is generally less important.

Through engagement with a consumer-focused research methods course, students become systematic interrogators. They start to ask more appropriate and refined questions about a study. By the end of the course, students can clearly explain why a causal claim needs an experiment to support it. They know how to evaluate whether a variable has been measured well. They know when it’s appro- priate to call for more participants in a study. And they can explain when a study must have a representative sample and when such a sample is not needed.

What About Future Researchers? This book can also be used to teach the flip side of the question: How can produc- ers of research design better studies? The producer angle is presented so that stu- dents will be prepared to design studies, collect data, and write papers in courses that prioritize these skills. Producer skills are crucial for students headed for Ph.D. study, and they are sometimes required by advanced coursework in the undergraduate major.

Such future researchers will find sophisticated content, presented in an accessible, consistent manner. They will learn the difference between media- tion (Chapter 9) and moderation (Chapters 8 and 9), an important skill in theory building and theory testing. They will learn how to design and interpret factorial designs, even up to three-way interactions (Chapter 12). And in the common event that a student-run study fails to work, one chapter helps them explore the possi- ble reasons for a null effect (Chapter 11). This book provides the basic statistical background, ethics coverage, and APA-style notes for guiding students through study design and execution.

Organization The fourteen chapters are arranged in six parts. Part I (Chapters 1–3) includes introductory chapters on the scientific method and the three claims, four validities framework. Part II (Chapters 4–5) covers issues that matter for any study: research

xiSupport for Students and Instructors

ethics and good measurement. Parts III–V (Chapters 6–12) correspond to each of the three claims (frequency, association, and causal). Part VI (Chapters 13–14) focuses on balancing research priorities.

Most of the chapters will be familiar to veteran instructors, including chapters on measurement, experimentation, and factorial designs. However, unlike some methods books, this one devotes two full chapters to correlational research (one on bivariate and one on multivariate studies), which help students learn how to interpret, apply, and interrogate different types of association claims, one of the common types of claims they will encounter.

There are three supplementary chapters, on Descriptive Statistics, Inferential Statistics, and APA-Style Reports and Conference Posters. These chapters provide a review for students who have already had statistics and provide the tools they need to create research reports and conference posters.

Two appendices—Random Numbers and How to Use Them, and Statistical Tables—provide reference tools for students who are conducting their own research.

Support for Students and Instructors The book’s pedagogical features emphasize active learning and repetition of the most important points. Each chapter begins with high-level learning objectives— major skills students should expect to remember even “a year from now.” Impor- tant terms in a chapter are introduced in boldface. The Check Your Understanding questions at the end of each major section provide basic questions that let students revisit key concepts as they read. Each chapter ends with multiple-choice Review Questions for retrieval practice, and a set of Learning Actively exercises that encourage students to apply what they learned. (Answers are provided at the end of the book.) A master table of the three claims and four validities appears inside the book’s front cover to remind students of the scaffold for the course.

I believe the book works pedagogically because it spirals through the three claims, four validities framework, building in repetition and depth. Although each chapter addresses the usual core content of research methods, students are always reminded of how a particular topic helps them interrogate the key validities. The interleaving of content should help students remember and apply this questioning strategy in the future.

I have worked with W. W. Norton to design a support package for fel- low instructors and students. The online Interactive Instructor’s Guide offers in-class activities, models of course design, homework and final assignments, and chapter-by-chapter teaching notes, all based on my experience with the course. The book is accompanied by other ancillaries to assist both new and experienced research methods instructors, including a new InQuizitive online assessment tool, a robust test bank with over 750 questions, updated lecture and active learning slides, and more; for a complete list, see p. xix.

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Teachable Examples on the Everyday Research Methods Blog Students and instructors can find additional examples of psychological science in the news on my regularly updated blog, Everyday Research Methods (www .everydayresearchmethods.com; no password or registration required). Instruc- tors can use the blog for fresh examples to use in class, homework, or exams. Students can use the entries as extra practice in reading about research studies in psychology in the popular media. Follow me on Twitter to get the latest blog updates (@bmorling).

Changes in the Third Edition Users of the first and second editions will be happy to learn that the basic organi- zation, material, and descriptions in the text remain the same. The third edition provides several new studies and recent headlines. Inclusion of these new exam- ples means that instructors who assign the third edition can also use their favorite illustrations from past editions as extra examples while teaching.

In my own experience teaching the course, I found that students could often master concepts in isolation, but they struggled to bring them all together when reading a real study. Therefore, the third edition adds new Working It Through sections in several chapters (Chapters 3, 4, 5, 8, and 11). Each one works though a single study in depth, so students can observe how the chapter’s central concepts are integrated and applied. For instance, in Chapter 4, they can see how ethics concepts can be applied to a recent study that manipulated Facebook newsfeeds. The Working It Through material models the process students will probably use on longer class assignments.

Also new in the third edition, every figure has been redrawn to make it more visually appealing and readable. In addition, selected figures are annotated to help students learn how to interpret graphs and tables.

Finally, W. W. Norton’s InQuizitive online assessment tool is available with the third edition. InQuizitive helps students apply concepts from the textbook to practice examples, providing specific feedback on incorrect responses. Some questions require students to interpret tables and figures; others require them to apply what they’re learning to popular media articles.

Here is a detailed list of the changes made to each chapter.

http://www.everydayresearchmethods.com
http://www.everydayresearchmethods.com
xiiiChanges in the Third Edition

CHAPTER MAJOR CHANGES IN THE THIRD EDITION

1. Psychology Is a Way of Thinking

The heading structure is the same as in the second edition, with some updated examples. I replaced the facilitated communication example (still an excellent teaching example) with one on the Scared Straight program meant to keep adolescents out of the criminal justice system, based on a reviewer’s recommendation.

2. Sources of Information: Why Research Is Best and How to Find it

I simplified the coverage of biases of intuition. Whereas the second edition separated cognitive biases from motivated reasoning, the biases are now presented more simply. In addition, this edition aims to be clearer on the difference between the availability heuristic and the present/present bias. I also developed the coverage of Google Scholar.

3. Three Claims, Four Validities: Interrogation Tools for Consumers of Research

The three claims, four validities framework is the same, keeping the best teachable examples from the second edition and adding new examples from recent media. In response to my own students’ confusion, I attempted to clarify the difference between the type of study conducted (correlational or experimental) and the claims made about it. To this end, I introduced the metaphor of a gift, in which a journalist might “wrap” a correlational study in a fancy, but inappropriate, causal claim.

When introducing the three criteria for causation, I now emphasize that covariance is about the study’s results, while temporal precedence and internal validity are determined from the study’s method.

Chapter 3 includes the first new Working It Through section.

4. Ethical Guidelines for Psychology Research

I updated the section on animal research and removed the full text of APA Standard 8. There’s a new figure on the difference between plagiarism and paraphrasing, and a new example of research fabrication (the notorious, retracted Lancet article on vaccines and autism). A new Working It Through section helps students assess the ethics of a recent Facebook study that manipulated people’s newsfeeds.

5. Identifying Good Measurement

This chapter retains many of the teaching examples as the second edition. For clarity, I changed the discriminant validity example so the correlation is only weak (not both weak and negative). A new Working It Through section helps students apply the measurement concepts to a self-report measure of gratitude in relationships.

6. Surveys and Observations: Describing What People Do

Core examples are the same, with a new study illustrating the effect of leading questions (a poll on attitudes toward voter ID laws). Look for the new “babycam” example in the Learning Actively exercises.

7. Sampling: Estimating the Frequency of Behaviors and Beliefs

Look for new content on MTurk and other Internet-based survey panels. I updated the statistics on cell-phone-only populations, which change yearly. Finally, I added clarity on the difference between cluster and stratified samples and explained sample weighting.

I added the new keyword nonprobability sample to work in parallel with the term probability sample. A new table (Table 7.3) helps students group related terms.

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CHAPTER MAJOR CHANGES IN THE THIRD EDITION

8. Bivariate Correlational Research

This chapter keeps most of the second edition examples. It was revised to better show that association claims are separate from correlational methods. Look for improved moderator examples in this chapter. These new examples, I hope, will communicate to students that moderators change the relationship between variables; they do not necessarily reflect the level of one of the variables.

9. Multivariate Correlational Research

I replaced both of the main examples in this chapter. The new example of cross- lag panel design, on parental overpraise and child narcissism, has four time periods (rather than two), better representing contemporary longitudinal studies. In the multiple regression section, the recess example is replaced with one on adolescents in which watching sexual TV content predicts teen pregnancy. The present regression example is student-friendly and also has stronger effect sizes.

Look for an important change in Figure 9.13 aimed to convey that a moderator can be thought of as vulnerability. My own students tend to think something is a moderator when the subgroup is simply higher on one of the variables. For example, boys might watch more violent TV content and be higher on aggression, but that’s not the same as a moderator. Therefore, I have updated the moderator column with the moderator “parental discussion.” I hope this will help students come up with their own moderators more easily.

10. Introduction to Simple Experiments

The red/green ink example was replaced with a popular study on notetaking, comparing the effects of taking notes in longhand or on laptops. There is also a new example of pretest/posttest designs (a study on mindfulness training). Students sometimes are surprised when a real-world study has multiple dependent variables, so I’ve highlighted that more in the third edition. Both of the chapter’s opening examples have multiple dependent variables.

I kept the example on pasta bowl serving size. However, after Chapter 10 was typeset, some researchers noticed multiple statistical inconsistencies in several publications from Wansink’s lab (for one summary of the issues, see the Chronicle of Higher Education article, “Spoiled Science”). At the time of writing, the pasta study featured in Chapter 10 has not been identified as problematic. Nevertheless, instructors might wish to engage students in a discussion of these issues.

11. More on Experiments: Confounding and Obscuring Variables

The content is virtually the same, with the addition of two Working It Through sections. The first one is to show students how to work through Table 11.1 using the mindfulness study from Chapter 10. This is important because after seeing Table 11.1, students sometimes think their job is to find the flaw in any study. In fact, most published studies do not have major internal validity flaws. The second Working It Through shows students how to analyze a null result.

12. Experiments with More Than One Independent Variable

Recent work has suggested that context-specific memory effects are not robust, so I replaced the Godden and Baddeley factorial example on context-specific learning with one comparing the memory of child chess experts to adults.

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CHAPTER MAJOR CHANGES IN THE THIRD EDITION

13. Quasi-Experiments and Small-N Designs

I replaced the Head Start study for two reasons. First, I realized it’s not a good example of a nonequivalent control group posttest-only design, because it actually included a pretest! Second, the regression to the mean effect it meant to illustrate is rare and difficult to understand. In exchange, there is a new study on the effects of walking by a church.

In the small-N design section, I provided fresh examples of multiple baseline design and alternating treatment designs. I also replaced the former case study example (split-brain studies) with the story of H.M. Not only is H.M.’s story compelling (especially as told through the eyes of his friend and researcher Suzanne Corkin), the brain anatomy required to understand this example is also simpler than that of split- brain studies, making it more teachable.

14. Replication, Generalization, and the Real World

A significant new section and table present the so-called “replication crisis” in psychology. In my experience, students are extremely engaged in learning about these issues. There’s a new example of a field experiment, a study on the effect of radio programs on reconciliation in Rwanda.

Supplementary Chapters In the supplementary chapter on inferential statistics, I replaced the section on randomization tests with a new section on confidence intervals. The next edition of the book may transition away from null hypothesis significance testing to emphasize the “New Statistics” of estimation and confidence intervals. I welcome feedback from instructors on this potential change.

Changes in the Third Edition

xvi

Acknowledgments

Working on this textbook has been rewarding and enriching, thanks to the many people who have smoothed the way. To start, I feel fortunate to have collaborated with an author-focused company and an all-around great editor, Sheri Snavely. Through all three editions, she has been both optimistic and realistic, as well as savvy and smart. She also made sure I got the most thoughtful reviews possible and that I was supported by an excellent staff at Norton: David Bradley, Jane Searle, Rubina Yeh, Eve Sanoussi, Victoria Reuter, Alex Trivilino, Travis Carr, and Dena Diglio Betz. My developmental editor, Betsy Dilernia, found even more to refine in the third edition, making the language, as well as each term, figure, and refer- ence, clear and accurate.

I am also thankful for the support and continued enthusiasm I have received from the Norton sales management team: Michael Wright, Allen Clawson, Ashley Sherwood, Annie Stewart, Dennis Fernandes, Dennis Adams, Katie Incorvia, Jordan Mendez, Amber Watkins, Shane Brisson, and Dan Horton. I also wish to thank the science and media special- ists for their creativity and drive to ensure my book reaches a wide audience, and that all the media work for instructors and students.

I deeply appreciate the support of many col- leagues. My former student Patrick Ewell, now at Kenyon College, served as a sounding board for new examples and authored the content for InQuizitive. Eddie Brummelman and Stefanie Nelemans provided additional correlations for the cross-lag panel design in Chapter 9. My friend Carrie Smith authored the Test Bank for the past two editions and has made it

an authentic measure of quantitative reasoning (as well as sending me things to blog about). Catherine Burrows carefully checked and revised the Test Bank for the third edition. Many thanks to Sarah Ainsworth, Reid Griggs, Aubrey McCarthy, Emma McGorray, and Michele M. Miller for carefully and patiently fact-checking every word in this edition. My student Xiaxin Zhong added DOIs to all the refer- ences and provided page numbers for the Check Your Understanding answers. Thanks, as well, to Emily Stanley and Jeong Min Lee, for writing and revising the questions that appear in the Coursepack created for the course management systems. I’m grateful to Amy Corbett and Kacy Pula for reviewing the ques- tions in InQuizitive. Thanks to my students Matt Davila-Johnson and Jeong Min Lee for posing for photographs in Chapters 5 and 10.

The book’s content was reviewed by a cadre of talented research method professors, and I am grateful to each of them. Some were asked to review; others cared enough to send me comments or examples by e-mail. Their students are lucky to have them in the classroom, and my readers will benefit from the time they spent in improving this book:

Eileen Josiah Achorn, University of Texas, San Antonio Sarah Ainsworth, University of North Florida Kristen Weede Alexander, California State University,

Sacramento Leola Alfonso-Reese, San Diego State University Cheryl Armstrong, Fitchburg State University Jennifer Asmuth, Susquehanna University Kristin August, Rutgers University, Camden

xviiAcknowledgments

Jessica L. Barnack-Tavlaris, The College of New Jersey Gordon Bear, Ramapo College Margaret Elizabeth Beier, Rice University Jeffrey Berman, University of Memphis Brett Beston, McMaster University Alisa Beyer, Northern Arizona University Julie Boland, University of Michigan Marina A. Bornovalova, University of South Florida Caitlin Brez, Indiana State University Shira Brill, California State University, Northridge J. Corey Butler, Southwest Minnesota State University Ricardo R. Castillo, Santa Ana College Alexandra F. Corning, University of Notre Dame Kelly A. Cotter, California State University, Stanislaus Lisa Cravens-Brown, The Ohio State University Victoria Cross, University of California, Davis Matthew Deegan, University of Delaware Kenneth DeMarree, University at Buffalo Jessica Dennis, California State University, Los Angeles Nicole DeRosa, SUNY Upstate Golisano Children’s Hospital Rachel Dinero, Cazenovia College Dana S. Dunn, Moravian College C. Emily Durbin, Michigan State University Russell K. Espinoza, California State University, Fullerton Patrick Ewell, Kenyon College Iris Firstenberg, University of California, Los Angeles Christina Frederick, Sierra Nevada College Alyson Froehlich, University of Utah Christopher J. Gade, University of California, Berkeley Timothy E. Goldsmith, University of New Mexico Jennifer Gosselin, Sacred Heart University AnaMarie Connolly Guichard, California State University,

Stanislaus Andreana Haley, University of Texas, Austin Edward Hansen, Florida State University Cheryl Harasymchuk, Carleton University Richard A. Hullinger, Indiana State University Deborah L. Hume, University of Missouri Kurt R. Illig, University of St. Thomas Jonathan W. Ivy, Pennsylvania State University, Harrisburg W. Jake Jacobs, University of Arizona Matthew D. Johnson, Binghamton University Christian Jordan, Wilfrid Laurier University Linda Juang, San Francisco State University