Handbook of Meta-analysis in Ecology and Evolution / / ed. by Kerrie Mengersen, Jessica Gurevitch, Julia Koricheva.

• Superior document: Title is part of eBook package: De Gruyter Princeton University Press eBook-Package Backlist 2000-2013
• MitwirkendeR: Curtis, Peter S.,; Côté, Isabelle M.,; Gurevitch, Jessica,; Jennions, Michael D.,; Koricheva, Julia,; Lajeunesse, Marc J.,; Lau, Joseph,; Lortie, Christopher J.,; Mengersen, Kerrie,; Rosenberg, Michael S.,; Rothstein, Hannah R.,; Schmid, Christopher H.,; Stewart, Gavin B.,
• HerausgeberIn: Gurevitch, Jessica,; Koricheva, Julia,; Mengersen, Kerrie,
• Place / Publishing House: Princeton, NJ : : Princeton University Press, , [2013]; ©2013
• Year of Publication: 2013
• Edition: Core Textbook
• Language: English
• Physical Description: 1 online resource (520 p.) :; 51 line illus. 45 tables.
• Other title: Frontmatter --; Contents --; Preface --; Section I. Introduction and Planning --; 1. Place of Meta-analysis among Other Methods of Research Synthesis --; 2. The Procedure of Meta-analysis in a Nutshell --; Section II. Initiating a Meta-analysis --; 3. First Steps in Beginning a Meta-analysis --; 4. Gathering Data: Searching Literature and Selection Criteria --; 5. Extraction and Critical Appraisal of Data --; 6. Effect Sizes: Conventional Choices and Calculations --; 7. Using Other Metrics of Effect Size in Meta-analysis --; Section III. Essential Analytic Models and Methods --; 8. Statistical Models and Approaches to Inference --; 9. Moment and Least-S quares Based Approaches to Meta-analytic Inference --; 10. Maximum Likelihood Approaches to Meta-analysis --; 11. Bayesian Meta-analysis --; 12. Software for Statistical Meta-analysis --; Section IV. Statistical Issues and Problems --; 13. Recovering Missing or Partial Data from Studies: A Survey of Conversions and Imputations for Meta-analysis --; 14. Publication and Related Biases --; 15. Temporal Trends in Effect Sizes: Causes, Detection, and Implications --; 16. Statistical Models for the Meta-analysis of Nonindependent Data --; 17. Phylogenetic Nonindependence and Meta-analysis --; 18. Meta-analysis of Primary Data --; 19. Meta-analysis of Results from Multisite Studies --; Section V. Presentation and Interpretation of Results --; 20. Quality Standards for Research Syntheses --; 21. Graphical Presentation of Results --; 22. Power Statistics for Meta-analysis: Tests for Mean Effects and Homogeneity --; 23. Role of Meta-analysis in Interpreting the Scientific Literature --; 24. Using Meta-analysis to Test Ecological and Evolutionary Theory --; 25. History and Progress of Meta-analysis --; 26. Contributions of Meta-analysis to Conservation and Management --; 27. Conclusions: Past, Present, and Future of Meta-analysis in Ecology and Evolution --; Glossary --; Frequently Asked Questions --; References --; List of Contributors --; Subject Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9781400846184; 9783110442502
• DOI: 10.1515/9781400846184?locatt=mode:legacy
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: ed. by Kerrie Mengersen, Jessica Gurevitch, Julia Koricheva.

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