Bayesian Random-Effects Meta-Analysis Using the bayesmeta R Package
Dublin Core
Title
Bayesian Random-Effects Meta-Analysis Using the bayesmeta R Package
Subject
evidence synthesis, NNHM, between-study heterogeneity
Description
The random-effects or normal-normal hierarchical model is commonly utilized in a
wide range of meta-analysis applications. A Bayesian approach to inference is very attractive in this context, especially when a meta-analysis is based only on few studies. The
bayesmeta R package provides readily accessible tools to perform Bayesian meta-analyses
and generate plots and summaries, without having to worry about computational details.
It allows for flexible prior specification and instant access to the resulting posterior distributions, including prediction and shrinkage estimation, and facilitating for example quick
sensitivity checks. The present paper introduces the underlying theory and showcases its
usage
wide range of meta-analysis applications. A Bayesian approach to inference is very attractive in this context, especially when a meta-analysis is based only on few studies. The
bayesmeta R package provides readily accessible tools to perform Bayesian meta-analyses
and generate plots and summaries, without having to worry about computational details.
It allows for flexible prior specification and instant access to the resulting posterior distributions, including prediction and shrinkage estimation, and facilitating for example quick
sensitivity checks. The present paper introduces the underlying theory and showcases its
usage
Creator
Christian Röver
Source
https://www.jstatsoft.org/article/view/v093i06
Publisher
University Medical Center Göttingen
Date
April 2020
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Christian Röver, “Bayesian Random-Effects Meta-Analysis Using the bayesmeta R Package,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8125.