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DESCRIPTION
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Package: RoBMA
Title: Robust Bayesian Meta-Analyses
Version: 3.4.0
Maintainer: František Bartoš <[email protected]>
Authors@R: c(
person("František", "Bartoš", role = c("aut", "cre"),
email = "[email protected]", comment = c(ORCID = "0000-0002-0018-5573")),
person("Maximilian", "Maier", role = "aut",
email = "[email protected]", comment = c(ORCID = "0000-0002-9873-6096")),
person("Eric-Jan", "Wagenmakers", role = "ths",
comment = c(ORCID = "0000-0003-1596-1034")),
person("Joris", "Goosen", role = "ctb"),
person("Matthew", "Denwood", role="cph",
comment="Original copyright holder of some modified code where indicated."),
person("Martyn", "Plummer", role="cph",
comment="Original copyright holder of some modified code where indicated.")
)
Description: 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.
URL: https://fbartos.github.io/RoBMA/
BugReports: https://github.com/FBartos/RoBMA/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
SystemRequirements: JAGS >= 4.3.1 (https://mcmc-jags.sourceforge.io/)
NeedsCompilation: yes
Depends:
R (>= 4.0.0)
Imports:
BayesTools (>= 0.2.18),
runjags,
rjags,
stats,
graphics,
mvtnorm,
scales,
Rdpack,
rlang,
coda,
ggplot2
Suggests:
parallel,
metaBMA,
metafor,
weightr,
lme4,
fixest,
emmeans,
metadat,
testthat,
vdiffr,
knitr,
rmarkdown,
covr
LinkingTo:
mvtnorm
RdMacros: Rdpack
VignetteBuilder: knitr