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

Computes the posterior model probabilities for standard 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 non-informative or informative priors for the mean effect size and the heterogeneity coefficient. Moreover, using pre-compiled Stan models, meta-analysis with continuous and discrete moderators with Jeffreys-Zellner-Siow (JZS) priors can be fitted and tested. This allows to compute Bayes factors and perform Bayesian model averaging across random- and fixed-effects meta-analysis with and without moderators. For a primer on Bayesian model-averaged meta-analysis, see Gronau, Heck, Berkhout, Haaf, & Wagenmakers (2020, <doi:10.31234/osf.io/97qup>).

Version: 0.6.7
Depends: R (≥ 3.4.0), Rcpp (≥ 1.0.0), methods
Imports: bridgesampling, coda, LaplacesDemon, logspline, mvtnorm, RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), rstantools (≥ 2.1.1)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 1.0.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests: testthat, knitr, rmarkdown, spelling
Published: 2021-03-17
Author: Daniel W. Heck ORCID iD [aut, cre], Quentin F. Gronau [ctb], Eric-Jan Wagenmakers [ctb], Indrajeet Patil ORCID iD [ctb]
Maintainer: Daniel W. Heck <dheck at uni-marburg.de>
License: GPL-3
URL: https://github.com/danheck/metaBMA
NeedsCompilation: yes
SystemRequirements: GNU make
Language: en-US
Citation: metaBMA citation info
Materials: NEWS
In views: MetaAnalysis
CRAN checks: metaBMA results

Documentation:

Reference manual: metaBMA.pdf
Vignettes: metaBMA: Meta-Analysis with Bayesian Model Averaging

Downloads:

Package source: metaBMA_0.6.7.tar.gz
Windows binaries: r-devel: metaBMA_0.6.7.zip, r-release: metaBMA_0.6.7.zip, r-oldrel: metaBMA_0.6.7.zip
macOS binaries: r-release (arm64): metaBMA_0.6.7.tgz, r-oldrel (arm64): metaBMA_0.6.7.tgz, r-release (x86_64): metaBMA_0.6.7.tgz, r-oldrel (x86_64): metaBMA_0.6.7.tgz
Old sources: metaBMA archive

Reverse dependencies:

Reverse suggests: ggstatsplot, insight, parameters, RoBMA, statsExpressions

Linking:

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