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 gmail.com> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| CRAN checks: |
BayesOrdDesign results |
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