metaBMA: Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Computes the posterior model probabilities for four meta-analysis models (null model vs. alternative model assuming either fixed- or random-effects, respectively). These posterior probabilities are used to estimate the overall mean effect size as the weighted average of the mean effect size estimates of the random- and fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, & Wagenmakers (2017, <doi:10.1080/23743603.2017.1326760>). The user can define a wide range of noninformative or informative priors for the mean effect size and the heterogeneity coefficient. Funding for this research was provided by the Berkeley Initiative for Transparency in the Social Sciences, a program of the Center for Effective Global Action (CEGA), with support from the Laura and John Arnold Foundation.

Version: 0.3.9
Depends: R (≥ 3.0.0)
Imports: mvtnorm, logspline, coda, runjags, LaplacesDemon
Suggests: testthat, knitr
Published: 2017-08-04
Author: Daniel W. Heck [aut, cre], Quentin F. Gronau [aut], Eric-Jan Wagenmakers [aut]
Maintainer: Daniel W. Heck <heck at>
License: GPL-3
NeedsCompilation: no
SystemRequirements: JAGS (
Materials: NEWS
In views: MetaAnalysis
CRAN checks: metaBMA results


Reference manual: metaBMA.pdf
Vignettes: metaBMA: Model Averaging for Meta-Analysis
Package source: metaBMA_0.3.9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: metaBMA_0.3.9.tgz, r-oldrel: metaBMA_0.3.9.tgz
Old sources: metaBMA archive


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