Bayesian Group Sequential Design for Ordinal Data

The proposed group-sequential trial design is based on Bayesian methods for ordinal endpoints, including three methods, the proportional-odds-model (PO)-based, non-proportional-odds-model (NPO)-based, and PO/NPO switch-model-based designs, which makes our proposed methods generic to be able to deal with various scenarios. Richard J. Barker, William A. Link (2013) . Thomas A. Murray, Ying Yuan, Peter F. Thall, Joan H. Elizondo, Wayne L.Hofstetter (2018) . Chengxue Zhong, Haitao Pan, Hongyu Miao (2021) .


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install.packages("BayesOrdDesign")

0.1.0 by Chengxue Zhong, a month ago


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


Authors: Chengxue Zhong [aut, cre] , Haitao Pan [aut] , Hongyu Miao [aut]


Documentation:   PDF Manual  


GPL-2 license


Imports ordinal, schoolmath, tidyverse, fda, coda, gsDesign, superdiag, ggplot2, madness, rjmcmc, R2jags, rjags, methods

Suggests testthat


See at CRAN