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:	3.1.0
Depends:	R (≥ 4.0.0)
Imports:	BayesTools (≥ 0.2.16), runjags, rjags, stats, graphics, mvtnorm, scales, Rdpack, rlang, ggplot2
LinkingTo:	mvtnorm
Suggests:	parallel, metaBMA, metafor, weightr, lme4, fixest, metadat, testthat, vdiffr, knitr, rmarkdown, covr
Published:	2023-07-18
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 Hierarchical Bayesian Model-Averaged Meta-Analysis Informed Bayesian Model-Averaged Meta-Analysis in Medicine Reproducing Bayesian Model-Averaged Meta-Analysis Tutorial: Adjusting for Publication Bias in JASP and R - Selection Models, PET-PEESE, and Robust Bayesian Meta-Analysis

Downloads:

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

Linking:

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