RoBMA: Robust Bayesian Meta-Analyses

A framework for estimating ensembles of meta-analytic and meta-regression models (assuming either presence or absence of the effect, heterogeneity, publication bias, and moderators). 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 prior distributions for + the effect size, heterogeneity, publication bias (including selection models and PET-PEESE), and moderator components. The package provides convenient functions for summary, visualizations, and fit diagnostics.

Version:	3.3.0
Depends:	R (≥ 4.0.0)
Imports:	BayesTools (≥ 0.2.18), 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:	2025-01-15
DOI:	10.32614/CRAN.package.RoBMA
Author:	František Bartoš [aut, cre], Maximilian Maier [aut], Eric-Jan Wagenmakers [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) Fast Robust Bayesian Meta-Analysis via Spike and Slab Algorithm (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_3.3.0.tar.gz
Windows binaries:	r-devel: RoBMA_3.3.0.zip, r-release: RoBMA_3.3.0.zip, r-oldrel: RoBMA_3.3.0.zip
macOS binaries:	r-release (arm64): RoBMA_3.3.0.tgz, r-oldrel (arm64): RoBMA_3.3.0.tgz, r-release (x86_64): RoBMA_3.3.0.tgz, r-oldrel (x86_64): RoBMA_3.3.0.tgz
Old sources:	RoBMA archive

Linking:

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