Handbook of Meta-Analysis in Ecology and Evolution

Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts.

The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management.

• Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation
• Brings together experts from a broad range of fields
• Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species
• Helps you choose the right software
• Draws on numerous examples based on real biological datasets

"A superb guide to the conduct and interpretation of meta-analysis, from an exceptional team of international experts. This comprehensive manual covers essential concepts, steps, and standards for rigorous research synthesis in ecology and evolutionary biology. Its clear prose, helpful illustrations, and worked examples will be useful for beginners and experts alike. Highly recommended for use as a textbook or for self-study."--Julia Littell, Bryn Mawr College, coauthor of Systematic Reviews and Meta-Analysis

"This is a well-written and valuable book, one that is unique within biology. The use of meta-analysis in ecology and evolution has reached the point where there is a need for a comprehensive, single-volume text such as this."--Samuel M. Scheiner, coeditor of The Theory of Ecology

"This book provides readers with a complete picture of the state of meta-analysis in ecology, evolution, and conservation biology today. It will help to raise the bar on the quality of meta-analytical research in the field, as well as improving research synthesis in general. This is the first book on the subject written for ecologists and environmental scientists."--Michael Dietze, Boston University

Julia Koricheva is Professor of Ecology at Royal Holloway, University of London. Jessica Gurevitch is Professor of Ecology and Evolution at Stony Brook University, State University of New York. Kerrie Mengersen is Research Professor of Statistics at Queensland University of Technology.

Preface xi

SECTION I: Introduction & Planning

1. Place of Meta-analysis among Other Methods of Research Synthesis 3

Julia Koricheva & Jessica Gurevitch

2. The Procedure of Meta-analysis in a Nutshell 14

Isabelle M. C?t? & Michael D. Jennions

SECTION II : Initiating a Meta-analysis

3. First Steps in Beginning a Meta-analysis 27

Gavin B. Stewart, Isabelle M. C?t?, Hannah R. Rothstein, & Peter S. Curtis

4. Gathering Data: Searching Literature & Selection Criteria 37

Isabelle M. C?t?, Peter S. Curtis, Hannah R. Rothstein, & Gavin B. Stewart

5. Extraction & Critical Appraisal of Data 52

Peter S. Curtis, Kerrie Mengersen, Marc J. Lajeunesse, Hannah R. Rothstein, & Gavin B. Stewart

6. Effect Sizes: Conventional Choices & Calculations 61

Michael S. Rosenberg, Hannah R. Rothstein, & Jessica Gurevitch

7. Using Other Metrics of Effect Size in Meta-analysis 72

Kerrie Mengersen & Jessica Gurevitch

SECTION III : Essential Analytic Models & Methods

8. Statistical Models & Approaches to Inference 89

Kerrie Mengersen, Christopher H. Schmid, Michael D. Jennions, & Jessica Gurevitch

9. Moment & Least-Squares Based Approaches to Meta-analytic Inference 108

Michael S. Rosenberg

10. Maximum Likelihood Approaches to Meta-analysis 125

Kerrie Mengersen & Christopher H. Schmid

11. Bayesian Meta-analysis 145

Christopher H. Schmid & Kerrie Mengersen

12. Software for Statistical Meta-analysis 174

Christopher H. Schmid, Gavin B. Stewart, Hannah R. Rothstein, Marc J. Lajeunesse, & Jessica Gurevitch

SECTION IV: Statistical Issues & Problems

13. Recovering Missing or Partial Data from Studies: A Survey of Conversions & Imputations for Meta-analysis 195

Marc J. Lajeunesse

14. Publication & Related Biases 207

Michael D. Jennions, Christopher J. Lortie, Michael S. Rosenberg, & Hannah R. Rothstein

15. Temporal Trends in Effect Sizes: Causes, Detection, & Implications 237

Julia Koricheva, Michael D. Jennions, & Joseph Lau

16. Statistical Models for the Meta-analysis of Nonindependent Data 255

Kerrie Mengersen, Michael D. Jennions, & Christopher H. Schmid

17. Phylogenetic Nonindependence & Meta-analysis 284

Marc J. Lajeunesse, Michael S. Rosenberg, & Michael D. Jennions

18. Meta-analysis of Primary Data 300

Kerrie Mengersen, Jessica Gurevitch, & Christopher H. Schmid

19. Meta-analysis of Results from Multisite Studies 313

Jessica Gurevitch

SECTION V: Presentation & Interpretation of Results

20. Quality St&ards for Research Syntheses 323

Hannah R. Rothstein, Christopher J. Lortie, Gavin B. Stewart, Julia Koricheva, & Jessica Gurevitch

21. Graphical Presentation of Results 339

Christopher J. Lortie, Joseph Lau, & Marc J. Lajeunesse

22. Power Statistics for Meta-analysis: Tests for Mean Effects & Homogeneity 348

Marc J. Lajeunesse

23. Role of Meta-analysis in Interpreting the Scientific Literature 364

Michael D. Jennions, Christopher J. Lortie, & Julia Koricheva

24. Using Meta-analysis to Test Ecological & Evolutionary Theory 381

Michael D. Jennions, Christopher J. Lortie, & Julia Koricheva

SECTION VI: Contributions of Meta-analysis in Ecology & Evolution

25. History & Progress of Meta-analysis 407

Joseph Lau, Hannah R. Rothstein, & Gavin B. Stewart

26. Contributions of Meta-analysis to Conservation & Management 420

Isabelle M. C?t? & Gavin B. Stewart

27. Conclusions: Past, Present, & Future of Meta-analysis in Ecology & Evolution 426

Jessica Gurevitch & Julia Koricheva

Glossary 433

Frequently Asked Questions 441

References 447

List of Contributors 487

Subject Index 489