BayesPPDSurv: Bayesian Power Prior Design for Survival Outcomes

Bayesian power/type I error calculation and model fitting using the power prior and the normalized power prior for time-to-event endpoints. The proportional hazards model with piecewise constant hazard (piecewise exponential) is implemented. The methodology and examples of applying the package are detailed in <doi:10.32614/RJ-2026-009>. 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:	1.0.5
Depends:	R (≥ 2.10)
Imports:	Rcpp, dplyr, tidyr
LinkingTo:	Rcpp, RcppArmadillo, RcppDist
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-09-28
DOI:	10.32614/CRAN.package.BayesPPDSurv
Author:	Yueqi Shen [aut, cre], Matthew A. Psioda [aut], Joseph G. Ibrahim [aut]
Maintainer:	Yueqi Shen <angieshen6 at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	yes
Materials:	NEWS
CRAN checks:	BayesPPDSurv results

Documentation:

Reference manual:

BayesPPDSurv.html , BayesPPDSurv.pdf

Downloads:

Package source:	BayesPPDSurv_1.0.5.tar.gz
Windows binaries:	r-devel: BayesPPDSurv_1.0.4.zip, r-release: BayesPPDSurv_1.0.4.zip, r-oldrel: BayesPPDSurv_1.0.5.zip
macOS binaries:	r-release (arm64): BayesPPDSurv_1.0.5.tgz, r-oldrel (arm64): BayesPPDSurv_1.0.5.tgz, r-release (x86_64): BayesPPDSurv_1.0.5.tgz, r-oldrel (x86_64): BayesPPDSurv_1.0.5.tgz
Old sources:	BayesPPDSurv archive

Linking:

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