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. 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: 1.0.3
Depends: R (≥ 3.5.0)
Imports: Rcpp, RcppNumerical
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppNumerical
Published: 2021-09-08
Author: Yueqi Shen [aut, cre], Matthew A. Psioda [aut], Joseph G. Ibrahim [aut]
Maintainer: Yueqi Shen <ys137 at live.unc.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
CRAN checks: BayesPPD results

Documentation:

Reference manual: BayesPPD.pdf

Downloads:

Package source: BayesPPD_1.0.3.tar.gz
Windows binaries: r-devel: BayesPPD_1.0.3.zip, r-devel-UCRT: BayesPPD_1.0.3.zip, r-release: BayesPPD_1.0.3.zip, r-oldrel: BayesPPD_1.0.3.zip
macOS binaries: r-release (arm64): BayesPPD_1.0.3.tgz, r-release (x86_64): BayesPPD_1.0.3.tgz, r-oldrel: BayesPPD_1.0.3.tgz
Old sources: BayesPPD archive

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