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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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Koricheva, Julia, 1967- (Editor ), Gurevitch, Jessica (Editor ), Mengersen, Kerrie L. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Princeton : Princeton University Press, 2013.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Handbook of meta-analysis in ecology and evolution /  |c edited by Julia Koricheva, Jessica Gurevitch, and Kerrie Mengersen. 
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505 0 |a Place of meta-analysis among other methods of research synthesis / Julia Koricheva and Jessica Gurevitch -- The procedure of meta-analysis in a nutshell / Isabelle M. Côté and Michael D. Jennions -- First steps in beginning a meta-analysis / Gavin B. Stewart, Isabelle M. Côté, Hannah R. Rothstein, and Peter S. Curtis -- Gathering data : searching literature and selection criteria / Isabelle M. Côté, Peter S. Curtis, Hannah R. Rothstein, and Gavin B. Stewart -- Extraction and critical appraisal of data / Peter S. Curtis, Kerrie Mengersen, Marc J. Lajeunesse, Hannah R. Rothstein, and Gavin B. Stewart -- Effect sizes : conventional choices and calculations / Michael S. Rosenberg, Hannah R. Rothstein, and Jessica Gurevitch -- Using other metrics of effect size in meta-analysis / Kerrie Mengersen and Jessica Gurevitch -- Statistical models and approaches to inference / Kerrie Mengersen, Christopher H. Schmid, Michael D. Jennions, and Jessica Gurevitch -- Moment and least-squares based approaches to meta-analytic inference / Michael S. Rosenberg -- Maximum likelihood approaches to meta-analysis / Kerrie Mengersen and Christopher H. Schmid -- Bayesian meta-analysis / Christopher H. Schmid and Kerrie Mengersen -- Software for statistical meta-analysis / Christopher H. Schmid, Gavin B. Stewart, Hannah R. Rothstein, Marc J. Lajeunesse, and Jessica Gurevitch -- Recovering missing or partial data from studies : a survey of conversions and imputations for meta-analysis / Marc J. Lajeunesse -- Publication and related biases / Michael D. Jennions, Christopher J. Lortie, Michael S. Rosenberg, and Hannah R. Rothstein -- Temporal trends in effect sizes : causes, detection, and implications / Julia Koricheva, Michael D. Jennions, and Joseph Lau -- Statistical models for the meta-analysis of nonindependent data / Kerrie Mengersen, Michael D. Jennions, and Christopher H. Schmid -- Phylogenetic nonindependence and meta-analysis / Marc J. Lajeunesse, Michael S. Rosenberg, and Michael D. Jennions -- Meta-analysis of primary data / Kerrie Mengersen, Jessica Gurevitch, and Christopher H. Schmid -- Meta-analysis of results from multisite studies / Jessica Gurevitch -- Quality standards for research syntheses / Hannah R. Rothstein, Christopher J. Lortie, Gavin B. Stewart, Julia Koricheva, and Jessica Gurevitch -- Graphical presentation of results / Christopher J. Lortie, Joseph Lau, and Marc J. Lajeunesse -- Power statistics for meta-analysis : tests for mean effects and homogeneity / Marc J. Lajeunesse -- Role of meta-analysis in interpreting the scientific literature / Michael D. Jennions, Christopher J. Lortie, and Julia Koricheva -- Using meta-analysis to test ecological and evolutionary theory / Michael D. Jennions, Christopher J. Lortie, and Julia Koricheva -- History and progress of meta-analysis / Joseph Lau, Hannah R. Rothstein, and Gavin B. Stewart -- Contributions of meta-analysis to conservation and management / Isabelle M. Côté and Gavin B. Stewart -- Conclusions : past, present, and future of meta-analysis in ecology and evolution / Jessica Gurevitch and Julia Koricheva. 
520 |a "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 "--  |c Provided by publisher. 
504 |a Includes bibliographical references (pages 447-485) and index. 
588 0 |a Print version record. 
546 |a In English. 
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650 0 |a Evolution  |x Mathematical models. 
650 0 |a Meta-analysis. 
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650 6 |a Méta-analyse. 
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650 7 |a Evolution  |x Mathematical models  |2 fast 
650 7 |a Meta-analysis  |2 fast 
700 1 |a Koricheva, Julia,  |d 1967-  |e editor. 
700 1 |a Gurevitch, Jessica,  |e editor. 
700 1 |a Mengersen, Kerrie L.,  |e editor. 
776 0 8 |i Print version:  |t Handbook of meta-analysis in ecology and evolution.  |d Princeton : Princeton University Press, [2013]  |z 9780691137285  |w (DLC) 2012041108  |w (OCoLC)820123442 
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