INTRODUCTION TO META-ANALYSIS. 2ND EDITION

• 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
Index 491

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)™

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