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HERO ID
5029243
Reference Type
Book/Book Chapter
Title
Chapter 11: Bayesian meta-analysis
Author(s)
Schmid, CH; Mengersen, K
Year
2013
Publisher
Princeton University Press
Location
Princeton, NJ
Book Title
Handbook of Meta-analysis in Ecology and Evolution
Language
English
DOI
10.23943/princeton/9780691137285.003.0011
Relationship(s)
is part of a larger document
5029185
Handbook of Meta-analysis in Ecology and Evolution
Abstract
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.
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