BayesPPDSurv: Bayesian Power Prior Design for Survival Data

Bayesian power/type I error calculation and model fitting using the power prior and the normalized power prior for proportional hazards models with piecewise constant hazard. The methodology and examples of applying the package are detailed in <doi:10.48550/arXiv.2404.05118>. The Bayesian clinical trial design methodology is described in Chen et al. (2011) <doi:10.1111/j.1541-0420.2011.01561.x>, and Psioda and Ibrahim (2019) <doi:10.1093/biostatistics/kxy009>. The proportional hazards model with piecewise constant hazard is detailed in Ibrahim et al. (2001) <doi:10.1007/978-1-4757-3447-8>.

Version: 1.0.3
Depends: R (≥ 2.10)
Imports: Rcpp, dplyr, tidyr
LinkingTo: Rcpp, RcppArmadillo, RcppDist
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-04-09
DOI: 10.32614/CRAN.package.BayesPPDSurv
Author: Yueqi Shen [aut, cre], Matthew A. Psioda [aut], Joseph G. Ibrahim [aut]
Maintainer: Yueqi Shen <ys137 at>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: NEWS
CRAN checks: BayesPPDSurv results


Reference manual: BayesPPDSurv.pdf


Package source: BayesPPDSurv_1.0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BayesPPDSurv_1.0.3.tgz, r-oldrel (arm64): BayesPPDSurv_1.0.3.tgz, r-release (x86_64): BayesPPDSurv_1.0.3.tgz, r-oldrel (x86_64): BayesPPDSurv_1.0.3.tgz
Old sources: BayesPPDSurv archive


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