Handbook of Meta-analysis in Ecology and Evolution

Handbook of Meta-analysis in Ecology and Evolution

Julia Koricheva, Jessica Gurevitch, and Kerrie Mengersen

Print publication date: 2017

ISBN: 9780691137285

Publisher: Princeton University Press


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 walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The book 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. The book is 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.

Table of Contents

Section I Introduction and Planning

2 The Procedure of Meta-analysis in a Nutshell

Isabelle M. Côté and Michael D. Jennions

Section II Initiating a Meta-analysis

3 First Steps in Beginning a Meta-analysis

Gavin B. Stewart, Isabelle M. Côté, Hannah R. Rothstein, and Peter S. Curtis

4 Gathering Data: Searching Literature and Selection Criteria

Isabelle M. Côté, Peter S. Curtis, Hannah R. Rothstein, and Gavin B. Stewart

5 Extraction and Critical Appraisal of Data

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

6 Effect Sizes: Conventional Choices and Calculations

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

7 Using Other Metrics of Effect Size in Meta-analysis

Kerrie Mengersen and Jessica Gurevitch

Section III Essential Analytic Models and Methods

8 Statistical Models and Approaches to Inference

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

10 Maximum Likelihood Approaches to Meta-analysis

Kerrie Mengersen and Christopher H. Schmid

11 Bayesian Meta-analysis

Christopher H. Schmid and Kerrie Mengersen

12 Software for Statistical Meta-analysis

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

Section IV Statistical Issues and Problems

14 Publication and Related Biases

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

15 Temporal Trends in Effect Sizes: Causes, Detection, and Implications

Julia Koricheva, Michael D. Jennions, and Joseph Lau

16 Statistical Models for the Meta-analysis of Nonindependent Data

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

17 Phylogenetic Nonindependence and Meta-analysis

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

18 Meta-analysis of Primary Data

Kerrie Mengersen, Jessica Gurevitch, and Christopher H. Schmid

Section V Presentation and Interpretation of Results

20 Quality Standards for Research Syntheses

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

21 Graphical Presentation of Results

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

23 Role of Meta-analysis in Interpreting the Scientific Literature

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

24 Using Meta-analysis to Test Ecological and Evolutionary Theory

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

Section VI Contributions of Meta-analysis in Ecology and Evolution

25 History and Progress of Meta-analysis

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