Update cookies preferences

Handbook of Meta-analysis in Ecology and Evolution [Hardback]

Edited by , Edited by , Edited by
  • Format: Hardback, 520 pages, height x width: 254x178 mm, weight: 1247 g, 51 line illus. 45 tables.
  • Pub. Date: 21-Apr-2013
  • Publisher: Princeton University Press
  • ISBN-10: 0691137285
  • ISBN-13: 9780691137285
Other books in subject:
  • Hardback
  • Price: 162,10 €
  • This book is not in stock. Book will arrive in about 2-4 weeks. Please allow another 2 weeks for shipping outside Estonia.
  • Quantity:
  • Add to basket
  • Delivery time 4-6 weeks
  • Add to Wishlist
  • Format: Hardback, 520 pages, height x width: 254x178 mm, weight: 1247 g, 51 line illus. 45 tables.
  • Pub. Date: 21-Apr-2013
  • Publisher: Princeton University Press
  • ISBN-10: 0691137285
  • ISBN-13: 9780691137285
Other books in subject:
"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 providesan 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 problemformulation 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 "--

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

Reviews

"[ T]his is a comprehensive and up-to-date compendium of all relevant aspects for meta-analysis conduction in ecology, evolution, and related topics. Scientists from these areas who already have some knowledge on meta-analysis will find valuable guidance."--Daniela Vetter, Quarterly Review of Biology

Preface xi
Section I Introduction and Planning
1 Place of Meta-analysis among Other Methods of Research Synthesis
3(11)
Julia Koricheva
Jessica Gurevitch
2 The Procedure of Meta-analysis in a Nutshell
14(13)
Isabelle M. Cote
Michael D. Jennions
Section II Initiating a Meta-analysis
3 First Steps in Beginning a Meta-analysis
27(10)
Gavin B. Stewart
Isabelle M. Cote
Hannah R. Rothstein
Peter S. Curtis
4 Gathering Data: Searching Literature and Selection Criteria
37(15)
Isabelle M. Cote
Peter S. Curtis
Hannah R. Rothstein
Gavin B. Stewart
5 Extraction and Critical Appraisal of Data
52(9)
Peter S. Curtis
Kerrie Mengersen
Marc J. Lajeunesse
Hannah R. Rothstein
Gavin B. Stewart
6 Effect Sizes: Conventional Choices and Calculations
61(11)
Michael S. Rosenberg
Hannah R. Rothstein
Jessica Gurevitch
7 Using Other Metrics of Effect Size in Meta-analysis
72(17)
Kerrie Mengersen
Jessica Gurevitch
Section III Essential Analytic Models and Methods
8 Statistical Models and Approaches to Inference
89(19)
Kerrie Mengersen
Christopher H. Schmid
Michael D. Jennions
Jessica Gurevitch
9 Moment and Least-Squares Based Approaches to Meta-analytic Inference
108(17)
Michael S. Rosenberg
10 Maximum Likelihood Approaches to Meta-analysis
125(20)
Kerrie Mengersen
Christopher H. Schmid
11 Bayesian Meta-analysis
145(29)
Christopher H. Schmid
Kerrie Mengersen
12 Software for Statistical Meta-analysis
174(21)
Christopher H. Schmid
Gavin B. Stewart
Hannah R. Rothstein
Marc J. Lajeunesse
Jessica Gurevitch
Section IV Statistical Issues and Problems
13 Recovering Missing or Partial Data from Studies: A Survey of Conversions and Imputations for Meta-analysis
195(12)
Marc J. Lajeunesse
14 Publication and Related Biases
207(30)
Michael D. Jennions
Christopher J. Lortie
Michael S. Rosenberg
Hannah R. Rothstein
15 Temporal Trends in Effect Sizes: Causes, Detection, and Implications
237(18)
Julia Koricheva
Michael D. Jennions
Joseph Lau
16 Statistical Models for the Meta-analysis of Nonindependent Data
255(29)
Kerrie Mengersen
Michael D. Jennions
Christopher H. Schmid
17 Phylogenetic Nonindependence and Meta-analysis
284(16)
Marc J. Lajeunesse
Michael S. Rosenberg
Michael D. Jennions
18 Meta-analysis of Primary Data
300(13)
Kerrie Mengersen
Jessica Gurevitch
Christopher H. Schmid
19 Meta-analysis of Results from Multisite Studies
313(10)
Jessica Gurevitch
Section V Presentation and Interpretation of Results
20 Quality Standards for Research Syntheses
323(16)
Hannah R. Rothstein
Christopher J. Lortie
Gavin B. Stewart
Julia Koricheva
Jessica Gurevitch
21 Graphical Presentation of Results
339(9)
Christopher J. Lortie
Joseph Lau
Marc J. Lajeunesse
22 Power Statistics for Meta-analysis: Tests for Mean Effects and Homogeneity
348(16)
Marc J. Lajeunesse
23 Role of Meta-analysis in Interpreting the Scientific Literature
364(17)
Michael D. Jennions
Christopher J. Lortie
Julia Koricheva
24 Using Meta-analysis to Test Ecological and Evolutionary Theory
381(26)
Michael D. Jennions
Christopher J. Lortie
Julia Koricheva
Section VI Contributions of Meta-analysis in Ecology and Evolution
25 History and Progress of Meta-analysis
407(13)
Joseph Lau
Hannah R. Rothstein
Gavin B. Stewart
26 Contributions of Meta-analysis to Conservation and Management
420(6)
Isabelle M. Cote
Gavin B. Stewart
27 Conclusions: Past, Present, and Future of Meta-analysis in Ecology and Evolution
426(7)
Jessica Gurevitch
Julia Koricheva
Glossary 433(8)
Frequently Asked Questions 441(6)
References 447(40)
List of Contributors 487(2)
Subject Index 489
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.