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 . 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) , and Psioda and Ibrahim (2019) . The normalized power prior is described in Duan et al. (2006) and Ibrahim et al. (2015) .


Reference manual

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install.packages("BayesPPD")

1.1.3 by Yueqi Shen, 2 years ago


Browse source code at https://github.com/cran/BayesPPD


Authors: Yueqi Shen [aut, cre] , Matthew A. Psioda [aut] , Joseph G. Ibrahim [aut]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports Rcpp

Suggests rmarkdown, knitr, testthat, ggplot2, kableExtra

Linking to Rcpp, RcppArmadillo, RcppEigen, RcppNumerical


Suggested by psborrow2.


See at CRAN