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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.3 |
rolling linux/jammy R-4.5 | BayesPPD_1.1.3.tar.gz |
449.4 KiB |
1.1.3 |
rolling linux/noble R-4.5 | BayesPPD_1.1.3.tar.gz |
458.3 KiB |
1.1.3 |
rolling source/ R- | BayesPPD_1.1.3.tar.gz |
105.0 KiB |
1.1.3 |
latest linux/jammy R-4.5 | BayesPPD_1.1.3.tar.gz |
449.4 KiB |
1.1.3 |
latest linux/noble R-4.5 | BayesPPD_1.1.3.tar.gz |
458.3 KiB |
1.1.3 |
latest source/ R- | BayesPPD_1.1.3.tar.gz |
105.0 KiB |
1.1.3 |
2026-04-26 source/ R- | BayesPPD_1.1.3.tar.gz |
105.0 KiB |
1.1.3 |
2026-04-23 source/ R- | BayesPPD_1.1.3.tar.gz |
105.0 KiB |
1.1.3 |
2026-04-09 windows/windows R-4.5 | BayesPPD_1.1.3.zip |
853.7 KiB |
1.1.3 |
2025-04-20 source/ R- | BayesPPD_1.1.3.tar.gz |
105.0 KiB |