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: 1.6-1
Depends: R (≥ 3.4.0), Rcpp (≥ 0.12.0), methods
Imports: assertthat, mvtnorm, Formula, checkmate, rstan (≥ 2.19.2), bayesplot (≥ 1.4.0), ggplot2, dplyr, stats, utils
LinkingTo: StanHeaders (≥ 2.19.0), rstan (≥ 2.19.2), BH (≥ 1.69.0), Rcpp (≥ 0.12.0), RcppEigen (≥
Suggests: rmarkdown, knitr, testthat (≥ 2.0.0), foreach, purrr, rstanarm (≥ 2.17.2), scales, tools, broom, tidyr, rstantools (≥ 2.0.0), parallel
Published: 2020-05-28
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


Reference manual: RBesT.pdf
Vignettes: Probability of Success with Co-Data (advanced)
Probability of Success at an Interim Analysis
Customizing RBesT plots
Getting started with RBesT (binary)
RBest for a Normal Endpoint
Using RBesT to reproduce Schmidli et al. "Robust MAP Priors"
Meta-Analytic-Predictive Priors for Variances
Package source: RBesT_1.6-1.tar.gz
Windows binaries: r-devel: RBesT_1.6-1.zip, r-release: RBesT_1.6-1.zip, r-oldrel: RBesT_1.6-1.zip
macOS binaries: r-release: RBesT_1.6-1.tgz, r-oldrel: RBesT_1.6-1.tgz
Old sources: RBesT archive


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