Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Christian Röver
Title: Bayesian Random-Effects Meta-Analysis Using the bayesmeta R Package
Abstract: 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.

Page views:: 2624. Submitted: 2017-11-23. Published: 2020-04-27.
Paper: Bayesian Random-Effects Meta-Analysis Using the bayesmeta R Package     Download PDF (Downloads: 929)
bayesmeta_2.5.tar.gz: R source package Download (Downloads: 73; 723KB)
v93i06.R: R replication code Download (Downloads: 101; 9KB)

DOI: 10.18637/jss.v093.i06

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.