Package: BayesPPD
Title: Bayesian Power Prior Design
Version: 1.1.3
Date: 2025-01-03
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_psioda@unc.edu"),
    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
        generalized linear models. Detailed examples of applying the
        package are available at <doi:10.32614/RJ-2023-016>. Models for
        time-to-event outcomes are implemented in the R package
        'BayesPPDSurv'. 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 normalized power
        prior is described in Duan et al. (2006) <doi:10.1002/env.752>
        and Ibrahim et al. (2015) <doi:10.1002/sim.6728>.
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.2.1
LazyData: true
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppNumerical
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), ggplot2, kableExtra
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2026-10-10 17:46:58 UTC; root
Author: Yueqi Shen [aut, cre], Matthew A. Psioda [aut], Joseph G.
        Ibrahim [aut]
Maintainer: Yueqi Shen <angieshen6@gmail.com>
Depends: R (>= 3.5.0)
Repository: https://angieshen6.r-universe.dev
Date/Publication: 2025-01-13 19:30:02 UTC
RemoteUrl: https://github.com/cran/BayesPPD
RemoteRef: HEAD
RemoteSha: a105b5c74c009b19c541310f436d70714827e36b