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 |
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