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>.
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>.
| Version: |
1.1.3 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppEigen, RcppNumerical |
| Suggests: |
rmarkdown, knitr, testthat (≥ 3.0.0), ggplot2, kableExtra |
| Published: |
2025-01-13 |
| DOI: |
10.32614/CRAN.package.BayesPPD |
| 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 |
| Citation: |
BayesPPD citation info |
| Materials: |
NEWS |
| CRAN checks: |
BayesPPD results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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