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RoBMA: Robust Bayesian Meta-Analyses

A framework for estimating ensembles of meta-analytic models (assuming either presence or absence of the effect, heterogeneity, and publication bias). The RoBMA framework uses Bayesian model-averaging to combine the competing meta-analytic models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual components (e.g., effect vs. no effect; Bartoš et al., 2022, <doi:10.1002/jrsm.1594>; Maier, Bartoš & Wagenmakers, 2022, <doi:10.1037/met0000405>). Users can define a wide range of non-informative or informative prior distributions for the effect size, heterogeneity, and publication bias components (including selection models and PET-PEESE). The package provides convenient functions for summary, visualizations, and fit diagnostics.

Version: 3.2.0
Depends: R (≥ 4.0.0)
Imports: BayesTools (≥ 0.2.17), runjags, rjags, stats, graphics, mvtnorm, scales, Rdpack, rlang, coda, ggplot2
LinkingTo: mvtnorm
Suggests: parallel, metaBMA, metafor, weightr, lme4, fixest, emmeans, metadat, testthat, vdiffr, knitr, rmarkdown, covr
Published: 2024-12-12
DOI: 10.32614/CRAN.package.RoBMA
Author: František Bartoš ORCID iD [aut, cre], Maximilian Maier ORCID iD [aut], Eric-Jan Wagenmakers ORCID iD [ths], Joris Goosen [ctb], Matthew Denwood [cph] (Original copyright holder of some modified code where indicated.), Martyn Plummer [cph] (Original copyright holder of some modified code where indicated.)
Maintainer: František Bartoš <f.bartos96 at gmail.com>
BugReports: https://github.com/FBartos/RoBMA/issues
License: GPL-3
URL: https://fbartos.github.io/RoBMA/
NeedsCompilation: yes
SystemRequirements: JAGS >= 4.3.1 (https://mcmc-jags.sourceforge.io/)
Citation: RoBMA citation info
Materials: README NEWS
In views: Bayesian, MetaAnalysis
CRAN checks: RoBMA results

Documentation:

Reference manual: RoBMA.pdf
Vignettes: Fitting Custom Meta-Analytic Ensembles (source, R code)
Hierarchical Bayesian Model-Averaged Meta-Analysis (source, R code)
Informed Bayesian Model-Averaged Meta-Analysis in Medicine (source, R code)
Informed Bayesian Model-Averaged Meta-Analysis with Binary Outcomes (source, R code)
Robust Bayesian Model-Averaged Meta-Regression (source, R code)
Reproducing Bayesian Model-Averaged Meta-Analysis (source, R code)
Tutorial: Adjusting for Publication Bias in JASP and R - Selection Models, PET-PEESE, and Robust Bayesian Meta-Analysis (source, R code)

Downloads:

Package source: RoBMA_3.2.0.tar.gz
Windows binaries: r-devel: RoBMA_3.2.0.zip, r-release: RoBMA_3.1.0.zip, r-oldrel: RoBMA_3.2.0.zip
macOS binaries: r-release (arm64): RoBMA_3.2.0.tgz, r-oldrel (arm64): RoBMA_3.2.0.tgz, r-release (x86_64): RoBMA_3.2.0.tgz, r-oldrel (x86_64): RoBMA_3.2.0.tgz
Old sources: RoBMA archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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