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metaBMA: Bayesian Model Averaging for Random and Fixed EffectsMeta-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 (2021, <doi:10.1177/25152459211031256>).

Version:0.6.9
Depends:R (≥ 4.0.0),Rcpp (≥ 1.0.0), methods
Imports:bridgesampling,coda,LaplacesDemon,logspline,mvtnorm,RcppParallel (≥ 5.0.1),rstan (≥ 2.26.0),rstantools (≥2.3.0)
LinkingTo:BH (≥ 1.78.0),Rcpp (≥ 1.0.0),RcppEigen (≥ 0.3.3.9.1),RcppParallel (≥ 5.0.1),rstan (≥ 2.26.0),StanHeaders (≥2.26.0)
Suggests:testthat,knitr,rmarkdown,spelling
Published:2023-09-13
DOI:10.32614/CRAN.package.metaBMA
Author:Daniel W. HeckORCID iD [aut, cre], Quentin F. Gronau [ctb], Eric-Jan Wagenmakers [ctb], Indrajeet PatilORCID iD [ctb]
Maintainer:Daniel W. Heck <daniel.heck at uni-marburg.de>
License:GPL-3
URL:https://github.com/danheck/metaBMA,https://danheck.github.io/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.html ,metaBMA.pdf
Vignettes:metaBMA: Meta-Analysis with Bayesian Model Averaging (source,R code)

Downloads:

Package source: metaBMA_0.6.9.tar.gz
Windows binaries: r-devel:metaBMA_0.6.9.zip, r-release:metaBMA_0.6.9.zip, r-oldrel:metaBMA_0.6.9.zip
macOS binaries: r-release (arm64):metaBMA_0.6.9.tgz, r-oldrel (arm64):metaBMA_0.6.9.tgz, r-release (x86_64):metaBMA_0.6.9.tgz, r-oldrel (x86_64):metaBMA_0.6.9.tgz
Old sources: metaBMA archive

Reverse dependencies:

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

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=metaBMAto link to this page.


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