Introduction to Meta-Analysis

1. Auflage 2009
ISBN: 978-0-470-05724-7
Verlag: Wiley John + Sons

Buch, Englisch, 452 Seiten, Format (B × H): 175 mm x 250 mm, Gewicht: 962 g

This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Introduction to Meta-Analysis:

* 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
* Clarifies concepts using text and figures, followed by formulas and examples
* Explains how to avoid common mistakes in meta-analysis
* Discusses controversies in meta-analysis
* Features a web site with additional material and exercises

A superb combination of lucid prose and informative graphics, written by four of the world's leading experts on all aspects of meta-analysis. Borenstein, Hedges, Higgins, and Rothstein 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, who used pre-publication versions of some of the chapters, 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

Introduction to Meta-Analysis is an excellent resource for novices and experts alike. The book provides a clear and comprehensive presentation of all basic and most advanced approaches to meta-analysis. This book will be referenced for decades. Michael A. McDaniel, Professor of Human Resources and Organizational Behavior, Virginia Commonwealth University

Autoren/Hrsg.

Borenstein, Michael

Hedges, Larry V.

Higgins, Julian P. T

Rothstein, Hannah R.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

List of Figures

List of Tables

Acknowledgements

Preface

PART 1: INTRODUCTION

1 HOW A META-ANALYSIS WORKS

2 WHY PERFORM A META-ANALYSIS

PART 2: EFFECT SIZE AND PRECISION

3 OVERVIEW

4 EFFECT SIZES BASED ON MEANS

5 EFFECT SIZES BASED ON BINARY DATA (2×2 TABLES)

6 EFFECT SIZES BASED ON CORRELATIONS

7 CONVERTING AMONG EFFECT SIZES

8 FACTORS THAT AFFECT PRECISION

9 CONCLUDING REMARKS

PART 3: FIXED-EFFECT VERSUS RANDOM-EFFECTS MODELS

10 OVERVIEW

11 FIXED-EFFECT MODEL

12 RANDOM-EFFECTS MODEL

13 FIXED EFFECT VERSUS RANDOM-EFFECTS MODELS

14 WORKED EXAMPLES (PART 1)

PART 4: HETEROGENEITY

15 OVERVIEW

16 IDENTIFYING AND QUANTIFYING HETEROGENEITY

17 PREDICTION INTERVALS

18 WORKED EXAMPLES (PART 2)

19 SUBGROUP ANALYSES

20 META-REGRESSION

21 NOTES ON SUBGROUP ANALYSES AND META-REGRESSION

PART 5: COMPLEX DATA STRUCTURES

22 OVERVIEW

23 INDEPENDENT SUBGROUPS WITHIN A STUDY

24 MULTIPLE OUTCOMES OR TIME POINTS WITHIN A STUDY

25 MULTIPLE COMPARISONS WITHIN A STUDY

26 NOTES ON COMPLEX DATA STRUCTURES

PART 6: OTHER ISSUES

27 OVERVIEW

28 VOTE COUNTING - A NEW NAME FOR AN OLD PROBLEM

29 POWER ANALYSIS FOR META-ANALYSIS

30 PUBLICATION BIAS

PART 7: ISSUES RELATED TO EFFECT SIZE

31 OVERVIEW

32 EFFECT SIZES RATHER THAN P -VALUES

33 SIMPSON'S PARADOX

34 GENERALITY OF THE BASIC INVERSE-VARIANCE METHOD

PART 8: FURTHER METHODS

35 OVERVIEW

36 META-ANALYSIS METHODS BASED ON DIRECTION AND P -VALUES

37 FURTHER METHODS FOR DICHOTOMOUS DATA

38 PSYCHOMETRIC META-ANALYSIS

PART 9: META-ANALYSIS IN CONTEXT

39 OVERVIEW

40 WHEN DOES IT MAKE SENSE TO PERFORM A META-ANALYSIS?

41 REPORTING THE RESULTS OF A META-ANALYSIS

42 CUMULATIVE META-ANALYSIS

43 CRITICISMS OF META-ANALYSIS

PART 10: RESOURCES AND SOFTWARE

44 SOFTWARE

45 BOOKS, WEB SITES AND PROFESSIONAL ORGANIZATIONS

INDEX