Package: BayesPPDSurv
Title: Bayesian Power Prior Design for Survival Data
Version: 1.0.4
Date: 2026-08-23
Authors@R: c(
    person(given = "Yueqi",
           family = "Shen",
           role = c("aut","cre"),
           email = "angieshen6@gmail.com"),
    person(given = "Matthew A.",
           family = "Psioda",
           role = c("aut"),
           email = "matt.a.psioda@gsk.com"),
    person(given = "Joseph G.",
           family = "Ibrahim",
           role = c("aut"),
           email = "ibrahim@bios.unc.edu"))
Description: 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>. 
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: Rcpp, dplyr, tidyr
LinkingTo: Rcpp, RcppArmadillo, RcppDist
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
LazyData: true
Config/testthat/edition: 3
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2026-08-23 23:48:26 UTC; angie
Author: Yueqi Shen [aut, cre],
  Matthew A. Psioda [aut],
  Joseph G. Ibrahim [aut]
Maintainer: Yueqi Shen <angieshen6@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-24 08:10:14 UTC
Built: R 4.5.2; aarch64-apple-darwin20; 2026-08-24 17:29:19 UTC; unix
Archs: BayesPPDSurv.so.dSYM
