A clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studiesThe first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated second edition includes new and expanded content on avoiding common mistakes in meta-analysis, understanding heterogeneity in effects, publication bias, and more. Several brand-new chapters provide a systematic "how to" approach to performing and reporting a meta-analysis from start to finish.Written by four of the world's foremost authorities on all aspects of meta-analysis, the new edition:* Outlines the role of meta-analysis in the research process* Shows how to compute effects sizes and treatment effects* Explains the fixed-effect and random-effects models for synthesizing data* Demonstrates how to assess and interpret variation in effect size across studies* Explains how to avoid common mistakes in meta-analysis* Discusses controversies in meta-analysis* Includes access to a companion website containing videos, spreadsheets, data files, free software for prediction intervals, and step-by-step instructions for performing analyses using Comprehensive Meta-Analysis (CMA)Download videos, class materials, and worked examples at Introduction-to-Meta-Analysis.com"This book offers the reader a unified framework for thinking about meta-analysis, and then discusses all elements of the analysis within that framework. The authors address a series of common mistakes and explain how to avoid them. As the editor-in-chief of the American Psychologist and former editor of Psychological Bulletin, I can say without hesitation that the quality of manuscript submissions reporting meta-analyses would be vastly better if researchers read this book."--Harris Cooper, Hugo L. Blomquist Distinguished Professor Emeritus of Psychology and Neuroscience, Editor-in-chief of the American Psychologist, former editor of Psychological Bulletin"A superb combination of lucid prose and informative graphics, the authors provide a refreshing departure from cookbook approaches with their clear explanations of the what and why of meta-analysis. The book is ideal as a course textbook or for self-study. My students raved about the clarity of the explanations and examples."--David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics"The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. The reader can comfortably skip the formulas and still understand their application and underlying motivation. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice."--Jesse A. Berlin, ScD

List of Tables xvList of Figures xixAcknowledgements xxvPreface xxviiPreface to the Second Edition xxxvWebsite xxxviiPart 1: Introduction1 How a Meta-Analysis Works 32 Why Perform a Meta-Analysis 9Part 2: Effect Size and Precision3 Overview 174 Effect Sizes Based On Means 215 Effect Sizes Based On Binary Data (2 × 2 Tables) 336 Effect Sizes Based On Correlations 397 Converting Among Effect Sizes 438 Factors That Affect Precision 499 Concluding Remarks 55Part 3: Fixed-Effect Versus Random-Effects Models10 Overview 5911 Fixed-Effect Model 6112 Random-Effects Model 6513 Fixed-Effect Versus Random-Effects Models 7114 Worked Examples (Part 1) 81Part 4: Heterogeneity15 Overview 9716 Identifying and Quantifying Heterogeneity 9917 Prediction Intervals 11918 Worked Examples (Part 2) 12719 An Intuitive Look At Heterogeneity 13920 Classifying Heterogeneity As Low, Moderate, Or High 155Part 5: Explaining Heterogeneity21 Subgroup Analyses 16122 Meta-Regression 19723 Notes On Subgroup Analyses and Meta-Regression 213Part 6: Putting It All In Context24 Looking At the Whole Picture 22325 Limitations of the Random-Effects Model 23326 Knapp-Hartung Adjustment 243Part 7: Complex Data Structures27 Overview 25328 Independent Subgroups Within a Study 25529 Multiple Outcomes or Time-Points Within A Study 26330 Multiple Comparisons Within a Study 27731 Notes On Complex Data Structures 281Part 8: Other Issues32 Overview 28733 Vote Counting - A New Name For An Old Problem 28934 Power Analysis For Meta-Analysis 29535 Publication Bias 313Part 9: Issues Related To Effect Size36 Overview 33537 Effect Sizes Rather Than P-Values 33738 Simpson's Paradox 34339 Generality of the Basic Inverse-Variance Method 349Part 10: Further Methods40 Overview 36141 Meta-Analysis Methods Based On Direction and P-Values 36342 Further Methods For Dichotomous Data 36943 Psychometric Meta-Analysis 377Part 11: Meta-Analysis In Context44 Overview 39145 When Does It Make Sense To Perform a Meta-Analysis? 39346 Reporting The Results of a Meta-Analysis 40147 Cumulative Meta-Analysis 40748 Criticisms of Meta-Analysis 41349 Comprehensive Meta-Analysis Software 42550 How To Explain the Results of An Analysis 443Part 12: Resources51 Software For Meta-Analysis 47152 Web Sites, Societies, Journals, and Books 473Web sites 473Professional societies 476Journals 476Special issues dedicated to meta-analysis 477Books on systematic review methods and meta-analysis 477References 479Index 491