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BayesPPD
View on CRAN: Click
here
Download and install BayesPPD package within the R console
Install from CRAN:
install.packages("BayesPPD")
Install from Github:
library("remotes")
install_github("cran/BayesPPD") Install by package version:
library("remotes")
install_version("BayesPPD", "1.1.3") Attach the package and use:
library("BayesPPD")
Maintained by
Yueqi Shen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-10
Latest Update: 2025-01-13
Description:
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 .
The Bayesian clinical trial design methodology is described in Chen et al. (2011)
, and Psioda and Ibrahim (2019)
. The normalized power prior is described in Duan et al. (2006)
and Ibrahim et al. (2015) .
How to cite:
Yueqi Shen (2021). BayesPPD: Bayesian Power Prior Design. R package version 1.1.3, https://cran.r-project.org/web/packages/BayesPPD. Accessed 25 Jun. 2026.
Previous versions and publish date:
Other packages that cited BayesPPD R package
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Other R packages that BayesPPD depends,
imports, suggests or enhances
Complete documentation for BayesPPD
Functions, R codes and Examples using
the BayesPPD R package
Some associated functions: BayesPPD-package . actg019 . actg036 . glm.fixed.a0 . glm.random.a0 . normalizing.constant . power.glm.fixed.a0 . power.glm.random.a0 . power.two.grp.fixed.a0 . power.two.grp.random.a0 . two.grp.fixed.a0 . two.grp.random.a0 .
Some associated R codes: BayesPPD-package.R . PWK_helper.R . PWK_main.R . RcppExports.R . data.R . glm_fixed.R . glm_random.R . two_grp_fixed.R . two_grp_random.R . Full BayesPPD package functions and examples
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