beastt: Bayesian Evaluation, Analysis, and Simulation Software Tools for Trials

Bayesian dynamic borrowing with covariate adjustment via inverse probability weighting for simulations and data analyses in clinical trials. This makes it easy to use propensity score methods to balance covariate distributions between external and internal data. This methodology based on Psioda et al (2025) <doi:10.1080/10543406.2025.2489285>.

Version: 0.0.3
Depends: R (≥ 4.1.0)
Imports: cli, cobalt, distributional, dplyr, generics, ggdist, ggplot2, methods, mixtools, purrr, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rlang, rstan (≥ 2.18.1), rstantools (≥ 2.4.0), stringr, tidyr
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests: knitr, mvtnorm, rmarkdown, spelling, testthat (≥ 3.0.0), tibble, vdiffr, survival
Published: 2025-05-15
Author: Christina Fillmore ORCID iD [aut, cre], Nate Bean ORCID iD [aut], Abi Terry [aut], Ben Arancibia [aut], GlaxoSmithKline Research & Development Limited [cph, fnd], Trustees of Columbia University [cph] (R/stanmodels.R, configure, configure.win)
Maintainer: Christina Fillmore <christina.e.fillmore at gsk.com>
BugReports: https://github.com/GSK-Biostatistics/beastt/issues
License: GPL (≥ 3)
URL: https://gsk-biostatistics.github.io/beastt/, https://github.com/GSK-Biostatistics/beastt
NeedsCompilation: yes
SystemRequirements: GNU make
Language: en-US
Materials: README NEWS
CRAN checks: beastt results

Documentation:

Reference manual: beastt.pdf
Vignettes: Binary Outcome (source, R code)
Normal Outcome (Known SD) (source, R code)
Time-to-Event Outcome (source, R code)

Downloads:

Package source: beastt_0.0.3.tar.gz
Windows binaries: r-devel: beastt_0.0.2.zip, r-release: beastt_0.0.2.zip, r-oldrel: beastt_0.0.2.zip
macOS binaries: r-release (arm64): beastt_0.0.3.tgz, r-oldrel (arm64): beastt_0.0.3.tgz, r-release (x86_64): beastt_0.0.2.tgz, r-oldrel (x86_64): beastt_0.0.2.tgz
Old sources: beastt archive

Linking:

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