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Handbook of Meta-analysis in Ecology and Evolution$
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Julia Koricheva, Jessica Gurevitch, and Kerrie Mengersen

Print publication date: 2013

Print ISBN-13: 9780691137285

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691137285.001.0001

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Bayesian Meta-analysis

Bayesian Meta-analysis

Chapter:
(p.145) 11 Bayesian Meta-analysis
Source:
Handbook of Meta-analysis in Ecology and Evolution
Author(s):

Christopher H. Schmid

Kerrie Mengersen

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691137285.003.0011

This chapter introduces a Bayesian approach to meta-analysis. It discusses the ways in which a Bayesian approach differs from the method of moments and maximum likelihood methods described in chapters 9 and 10, and summarizes the steps required for a Bayesian analysis. It shows that Bayesian methods provide the basis for a rich variety of very flexible models, explicit statements about uncertainty of model parameters, inclusion of other information relevant to an analysis, and direct probabilistic statements about parameters of interest. In a meta-analysis context, this allows for more straightforward accommodation of study-specific differences and similarities, nonnormality and other distributional features of the data, missing data, small studies, and so forth.

Keywords:   Bayesian approach, meta-analysis, Bayesian analysis, statistical inference

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