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.

Version: 0.6.2
Depends: R (≥ 3.4.0), Rcpp (≥ 1.0.0), methods
Imports: mvtnorm, logspline, coda, LaplacesDemon, rstan (≥ 2.18.1), rstantools (≥ 1.5.1), bridgesampling
LinkingTo: BH (≥ 1.69.0-1), Rcpp (≥ 1.0.0), RcppEigen (≥ 0.3.3.5.0), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests: testthat, knitr
Published: 2019-09-16
Author: Daniel W. Heck ORCID iD [aut, cre], Quentin F. Gronau [ctb]
Maintainer: Daniel W. Heck <heck at uni-mannheim.de>
License: GPL-3
URL: https://github.com/danheck/metaBMA
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: NEWS
In views: MetaAnalysis
CRAN checks: metaBMA results

Downloads:

Reference manual: metaBMA.pdf
Vignettes: metaBMA: Meta-Analysis with Bayesian Model Averaging
Package source: metaBMA_0.6.2.tar.gz
Windows binaries: r-devel: metaBMA_0.6.2.zip, r-release: metaBMA_0.6.2.zip, r-oldrel: metaBMA_0.6.2.zip
OS X binaries: r-release: metaBMA_0.6.2.tgz, r-oldrel: metaBMA_0.6.2.tgz
Old sources: metaBMA archive

Reverse dependencies:

Reverse imports: ggstatsplot

Linking:

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