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BayesPPD: Bayesian Power Prior Design

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>. 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>.

Version: 1.1.2
Depends: R (≥ 3.5.0)
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppNumerical
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0), ggplot2, kableExtra
Published: 2023-11-25
DOI: 10.32614/CRAN.package.BayesPPD
Author: Yueqi Shen [aut, cre], Matthew A. Psioda [aut], Joseph G. Ibrahim [aut]
Maintainer: Yueqi Shen <ys137 at live.unc.edu>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: NEWS
CRAN checks: BayesPPD results

Documentation:

Reference manual: BayesPPD.pdf
Vignettes: bayesppd-vignette

Downloads:

Package source: BayesPPD_1.1.2.tar.gz
Windows binaries: r-devel: BayesPPD_1.1.2.zip, r-release: BayesPPD_1.1.2.zip, r-oldrel: BayesPPD_1.1.2.zip
macOS binaries: r-release (arm64): BayesPPD_1.1.2.tgz, r-oldrel (arm64): BayesPPD_1.1.2.tgz, r-release (x86_64): BayesPPD_1.1.2.tgz, r-oldrel (x86_64): BayesPPD_1.1.2.tgz
Old sources: BayesPPD archive

Reverse dependencies:

Reverse suggests: psborrow2

Linking:

Please use the canonical form https://CRAN.R-project.org/package=BayesPPD to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.