Applied Meta-Analysis for Social Science Research

Noel A. Card

• Publisher: The Guilford Press
• Year: 2011
• Print ISBN: 9781462525003
• eBook ISBN: 9781609185015
• Topic: Psychology
• Subtopic: Statistics for Business & Economics
• Index: Psychology

Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs.

 

Table of contents

• Front Matter
• Title Page
• Copyright
• Dedication
• Series Editor’s Note
• Preface and Acknowledgments
• Contents
• Part I The Blueprint Planning and Preparinga Meta‑Analytic Review
• Chapter 1 An Introduction to Meta-Analysis
• 1.1 The Need for Research Synthesis in the Social Sciences
• 1.2 Basic Terminology
• 1.3 A Brief History of Meta‑Analysis
• 1.4 The Scientific Process of Research Synthesis
• 1.5 An Overview of the Book
• 1.6 Practical Matters: A Note on Software and Information Management
• 1.7 Summary
• 1.8 Recommended Readings
• Chapter 2 Questions That Can and Questions That Cannot Be Answered through Meta-Analysis
• 2.1 Identifying Goals and Research Questions for Meta‑Analysis
• 2.2 The Limits of Primary Research and the Limits of Meta‑Analytic Synthesis
• 2.3 Critiques of Meta‑Analysis: When Are They Valid and When Are They Not?
• 2.4 Practical Matters: The Reciprocal Relation between Planning and Conducting a Meta‑Analysis
• 2.5 Summary
• 2.6 Recommended Readings
• Chapter 3 Searching the Literature
• 3.1 Developing and Articulating a Sampling Frame
• 3.2 Inclusion and Exclusion Criteria
• 3.3 Finding Relevant Literature
• 3.4 Reality Checking: Is My Search Adequate?
• 3.5 Practical Matters: Beginning a Meta‑Analytic Database
• 3.6 Summary
• 3.7 Recommended Readings
• Part II The Building Blocks Coding Individual Studies
• Chapter 4 Coding Study Characteristics
• 4.1 Identifying Interesting Moderators
• 4.2 Coding Study “Quality”
• 4.3 Evaluating Coding Decisions
• 4.4 Practical Matters: Creating an Organized Protocol for Coding
• 4.5 Summary
• 4.6 Recommended Readings
• Chapter 5 Basic Effect Size Computation
• 5.1 The Common Metrics: Correlation, Standardized Mean Difference, and Odds Ratio
• 5.2 Computing r from Commonly Reported Results
• 5.3 Computing g from Commonly Reported Results
• 5.4 Computing o from Commonly Reported Results
• 5.5 Comparisons among r, g, and o
• 5.6 Practical Matters: Using Effect Size Calculators and Meta‑Analysis Programs
• 5.7 Summary
• 5.8 Recommended Readings
• Chapter 6 Corrections to Effect Sizes
• 6.1 The Controversy of Correction
• 6.2 Artifact Corrections to Consider
• 6.3 Practical Matters: When (and How) to Correct: Conceptual, Methodological, and Disciplinary Considerations
• 6.4 Summary
• 6.5 Recommended Readings
• Chapter 7 Advanced and Unique Effect Size Computation
• 7.1 Describing Single Variables
• 7.2 When the Metric Is Meaningful: Raw Difference Scores
• 7.3 Regression Coefficients and Similar Multivariate Effect Sizes
• 7.4 Miscellaneous Effect Sizes
• 7.5 Practical Matters: The Opportunities and Challenges of Meta‑Analyzing Unique Effect Sizes
• 7.6 Summary
• 7.7 Recommended Readings
• Part III Putting the Pieces Together Combining and Comparing Effect Sizes
• Chapter 8 Basic Computations Computing Mean Effect Size and Heterogeneity around This Mean
• 8.1 The Logic of Weighting
• 8.2 Measures of Central Tendency in Effect Sizes
• 8.3 Inferential Testing and Confidence Intervals of Average Effect Sizes
• 8.4 Evaluating Heterogeneity among Effect Sizes
• 8.5 Practical Matters: Nonindependence among Effect Sizes
• 8.6 Summary
• 8.7 Recommended Readings
• Chapter 9 Explaining Heterogeneity among Effect Sizes Moderator Analyses
• 9.1 Categorical Moderators
• 9.2 Continuous Moderators
• 9.3 A General Multiple Regression Framework for Moderation
• 9.4 An Alternative SEM Approach
• 9.5 Practical Matters: The Limits of Interpreting Moderators in Meta‑Analysis
• 9.6 Summary
• 9.7 Recommended Readings
• Chapter 10 Fixed‑, Random‑, and Mixed‑Effects Models
• 10.1 Differences among Models
• 10.2 Analyses of Random‑Effects Models
• 10.3 Mixed‑Effects Models
• 10.4 A Structural Equation Modeling Approach to Random‑ and Mixed‑Effects Models
• 10.5 Practical Matters: Which Model Should I Use?
• 10.6 Summary
• 10.7 Recommended Readings
• Chapter 11 Publication Bias
• 11.1 The Problem of Publication Bias
• 11.2 Managing Publication Bias
• 11.3 Practical Matters: What Impact Do Sampling Biases Have on Meta‑Analytic Conclusions?
• 11.4 Summary
• 11.5 Recommended Readings
• Chapter 12 Multivariate Meta‑Analytic Models
• 12.1 Meta‑analysis to Obtain Sufficient Statistics
• 12.2 Two Approaches to Multivariate Meta‑Analysis
• 12.3 Practical Matters: The Interplay between Meta‑Analytic Models and Theory
• 12.4 Summary
• 12.5 Recommended Readings
• Part IV The Final Product Reporting Meta‑Analytic Results
• Chapter 13 Writing Meta‑Analytic Results
• 13.1 Dimensions of Literature Reviews, Revisited
• 13.2 What to Report and Where to Report It
• 13.3 Using Tables and Figures in Reporting Meta‑Analyses
• 13.4 Practical Matters: Avoiding Common Problems in Reporting Results of Meta‑Analyses
• 13.5 Summary
• 13.6 Recommended Readings
• References
• Author Index
• Subject Index
• About the Author