Package: RoBMA
Title: Robust Bayesian Meta-Analyses
Version: 1.1.0
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")
    )
Description: A framework for estimating ensembles of meta-analytic models
    (assuming either presence or absence of the effect, heterogeneity, and
    publication bias) and using Bayesian model averaging to combine them. The
    ensembles use Bayes factors to test for the presence or absence of the
    individual components (e.g., effect vs. no effect) and model-averages
    parameter estimates based on posterior model probabilities
    (Maier, Bartoš & Wagenmakers, 2020, <doi:10.31234/osf.io/u4cns>). The user can
    define a wide range of non-informative or informative priors for the
    effect size, heterogeneity, and weight functions. 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
RoxygenNote: 7.1.1
Imports: runjags, bridgesampling, rjags, coda, psych, stats, graphics,
        extraDistr, scales, DPQ, callr, Rdpack
Suggests: ggplot2, parallel, rstan, metaBMA, testthat, vdiffr, knitr,
        rmarkdown
RdMacros: Rdpack
LinkingTo: BH
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-10-29 22:59:44 UTC; fbart
Author: František Bartoš [aut, cre] (<https://orcid.org/0000-0002-0018-5573>),
  Maximilian Maier [aut] (<https://orcid.org/0000-0002-9873-6096>),
  Eric-Jan Wagenmakers [ths] (<https://orcid.org/0000-0003-1596-1034>),
  Joris Goosen [ctb]
Repository: CRAN
Date/Publication: 2020-10-30 05:20:07 UTC
