RBesT: R Bayesian Evidence Synthesis Tools

Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> for details on the methodology.

Version: 1.6-2
Depends: R (≥ 3.4.0)
Imports: methods, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.19.3), rstantools (≥ 2.1.1), assertthat, mvtnorm, Formula, checkmate, bayesplot (≥ 1.4.0), ggplot2, dplyr, stats, utils
LinkingTo: BH (≥ 1.72.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.19.3), StanHeaders (≥ 2.19.0)
Suggests: rmarkdown, knitr, testthat (≥ 2.0.0), foreach, purrr, rstanarm (≥ 2.17.2), scales, tools, broom, tidyr, parallel
Published: 2021-09-03
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Beat Neuenschwander [ctb], Heinz Schmidli [ctb], Baldur Magnusson [ctb], Yue Li [ctb], Satrajit Roychoudhury [ctb], Trustees of Columbia University [cph] (R/stanmodels.R, configure, configure.win)
Maintainer: Sebastian Weber <sebastian.weber at novartis.com>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make, pandoc (>= 1.12.3), pandoc-citeproc
Materials: NEWS
In views: MetaAnalysis
CRAN checks: RBesT results

Downloads:

Reference manual: RBesT.pdf
Vignettes: Customizing RBesT plots
RBest for a Normal Endpoint
Getting started with RBesT (binary)
Probability of Success with Co-Data (advanced)
Probability of Success at an Interim Analysis
Using RBesT to reproduce Schmidli et al. "Robust MAP Priors"
Meta-Analytic-Predictive Priors for Variances
Package source: RBesT_1.6-2.tar.gz
Windows binaries: r-devel: RBesT_1.6-2.zip, r-devel-UCRT: RBesT_1.6-2.zip, r-release: RBesT_1.6-2.zip, r-oldrel: RBesT_1.6-2.zip
macOS binaries: r-release (arm64): RBesT_1.6-2.tgz, r-release (x86_64): RBesT_1.6-2.tgz, r-oldrel: RBesT_1.6-2.tgz
Old sources: RBesT archive

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