BayesOrdDesign: 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) <doi:10.1080/00031305.2013.791644>. Thomas A. Murray, Ying Yuan, Peter F. Thall, Joan H. Elizondo, Wayne L.Hofstetter (2018) <doi:10.1111/biom.12842>. Chengxue Zhong, Haitao Pan, Hongyu Miao (2021) <doi:10.48550/arXiv.2108.06568>.

Version: 0.1.2
Depends: R (≥ 3.3.0)
Imports: ordinal, schoolmath, coda, gsDesign, superdiag, ggplot2, madness, rjmcmc, R2jags, rjags, methods
Suggests: testthat (≥ 3.0.0)
Published: 2022-11-14
DOI: 10.32614/CRAN.package.BayesOrdDesign
Author: Chengxue Zhong [aut, cre], Haitao Pan [aut], Hongyu Miao [aut]
Maintainer: Chengxue Zhong <czhong9106 at>
License: GPL-2
NeedsCompilation: no
CRAN checks: BayesOrdDesign results


Reference manual: BayesOrdDesign.pdf


Package source: BayesOrdDesign_0.1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BayesOrdDesign_0.1.2.tgz, r-oldrel (arm64): BayesOrdDesign_0.1.2.tgz, r-release (x86_64): BayesOrdDesign_0.1.2.tgz, r-oldrel (x86_64): BayesOrdDesign_0.1.2.tgz
Old sources: BayesOrdDesign archive


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