DESCRIPTION

Package: RoBMA
Title: Robust Bayesian Meta-Analyses
Version: 3.1.0
Maintainer: František Bartoš <f.bartos96@gmail.com>
Authors@R: c( 
    person("František", "Bartoš",     role = c("aut", "cre"),
    email   = "f.bartos96@gmail.com", comment = c(ORCID = "0000-0002-0018-5573")),
    person("Maximilian", "Maier",     role = "aut",
    email   = "maximilianmaier0401@gmail.com", 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 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.
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: 7.2.3
SystemRequirements: JAGS >= 4.3.1 (https://mcmc-jags.sourceforge.io/)
NeedsCompilation: yes
Depends:
    R (>= 4.0.0)
Imports:
    BayesTools (>= 0.2.16),
    runjags,
    rjags,
    stats,
    graphics,
    mvtnorm,
    scales,
    Rdpack,
    rlang,
    ggplot2
Suggests:
    parallel,
    metaBMA,
    metafor,
    weightr,
    lme4,
    fixest,
    metadat,
    testthat,
    vdiffr,
    knitr,
    rmarkdown,
    covr
LinkingTo:
    mvtnorm
RdMacros: Rdpack
VignetteBuilder: knitr