This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. The 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)(TM)

  Download videos, class materials, and worked examples at www.Introduction-to-Meta-Analysis.com

  Autorentext
  Michael Borenstein is the Director of Biostat, a leading developer of statistical software. He is the primary developer of Comprehensive Meta-Analysis (CMA), the world's most widely used program for meta-analysis. He is the recipient of numerous grants from the NIH to develop methods, software, and educational materials for meta-analysis. He has lectured widely on meta-analysis, including at the NIH, CDC, and FDA. Larry V. Hedges is Board of Trustees Professor of Statistics and Education and Social Policy, Professor of Psychology, Professor of Medical Social Sciences, and IPR Fellow, Northwestern University, USA. He is a national leader in the fields of educational statistics and evaluation and is an elected member of many leading associations. Julian P.T. Higgins is Professor of Evidence Synthesis at the University of Bristol, UK, and a National Institute for Health Research (NIHR) Senior Investigator. He has had numerous core roles in the Cochrane Collaboration, including editing its methodological Handbook since 2003. His many contributions to meta-analysis include the foundation of network meta-analysis, methods for describing and explaining heterogeneity and a general framework for individual participant data meta-analysis. He is a Highly Cited Researcher with over a quarter of a million citations to his work and has been a recipient of the Ingram Olkin Award for distinguished lifetime achievement in research synthesis methodology. Hannah R. Rothstein is Professor of Management at Baruch College and the Graduate Center of the City University of New York. She is a Fellow of the American Psychological Association and a past President of the Society for Research Synthesis Methodology. She is former Editor-in-Chief of Research Synthesis Methods and serves on the editorial boards of Psychological Bulletin, Psychological Methods, and Organizational Research Methods. Professor Rothstein is a co-developer of the Comprehensive Meta-Analysis software and has published numerous systematic reviews and meta-analyses.

  Inhalt

  List of Tables xv

  List of Figures xix

  Acknowledgements xxv

  Preface xxvii

  Preface to the Second Edition xxxv

  Website xxxvii

  Part 1: Introduction

  1 How a Meta-Analysis Works 3

  2 Why Perform a Meta-Analysis 9

  Part 2: Effect Size and Precision

  3 Overview 17

  4 Effect Sizes Based On Means 21

  5 Effect Sizes Based On Binary Data (2 × 2 Tables) 33

  6 Effect Sizes Based On Correlations 39

  7 Converting Among Effect Sizes 43

  8 Factors That Affect Precision 49

  9 Concluding Remarks 55

  Part 3: Fixed-Effect Versus Random-Effects Models

  10 Overview 59

  11 Fixed-Effect Model 61

  12 Random-Effects Model 65

  13 Fixed-Effect Versus Random-Effects Models 71

  14 Worked Examples (Part 1) 81

  Part 4: Heterogeneity

  15 Overview 97

  16 Identifying and Quantifying Heterogeneity 99

  17 Prediction Intervals 119

  18 Worked Examples (Part 2) 127

  19 An Intuitive Look At Heterogeneity 139

  20 Classifying Heterogeneity As Low, Moderate, Or High 155

  Part 5: Explaining Heterogeneity

  21 Subgroup Analyses 161

  22 Meta-Regression 197

  23 Notes On Subgroup Analyses and Meta-Regression 213

  Part 6: Putting It All In Context

  24 Looking At the Whole Picture 223

  25 Limitations of the Random-Effects Model 233

  26 Knapp-Hartung Adjustment 243

  Part 7: Complex Data Structures

  27 Overview 253

  28 Independent Subgroups Within a Study 255

  29 Multiple Outcomes or Time-Points Within A Study 263

  30 Multiple Comparisons Within a Study 277

  31 Notes On Complex Data Structures 281

  Part 8: Other Issues

  32 Overview 287

  33 Vote Counting - A New Name For An Old Problem 289

  34 Power Analysis For Meta-Analysis 295

  35 Publication Bias 313

  Part 9: Issues Related To Effect Size

  36 Overview 335

  37 Effect Sizes Rather Than P-Values 337

  38 Simpson's Paradox 343

  39 Generality of the Basic Inverse-Variance Method 349

  Part 10: Further Methods

  40 Overview 361

  41 Meta-Analysis Methods Based On Direction and P-Values 363

  42 Further Methods For Dichotomous Data 369

  43 Psychometric Meta-Analysis 377

  Part 11: Meta-Analysis In Context

  44 Overview 391

  45 When Does It Make Sense To Perform a Meta-Analysis? 393

  46 Reporting The Results of a Meta-Analysis 401

  47 Cumulative Meta-Analysis 407

  48 Criticisms of Meta-Analysis 413

  49 Comprehensive Meta-Analysis Software 425

  50 How To Explain the Results of An Analysis 443

  Part 12: Resources

  51 Software For Meta-Analysis 471

  52 Web Sites, Societies, Journals, and Books 473

  Web sites 473

  Professional societies 476

  Journals 476

  Special issues dedicated to meta-analysis 477

  Books on systematic review methods and meta-analysis 477

  References 479

  Index 491