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Provides the design of multi-group phase II clinical trials with binary outcomes using the hierarchical Bayesian classification and information sharing (BaCIS) model. Subgroups are classified into two clusters on the basis of their outcomes mimicking the hypothesis testing framework. Subsequently, information sharing takes place within subgroups in the same cluster, rather than across all subgroups. This method can be applied to the design and analysis of multi-group clinical trials with binary outcomes. Reference: Nan Chen and J. Jack Lee (2019) <doi:10.1002/bimj.201700275>.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.3.0) |
| Imports: | rjags |
| Published: | 2020-06-05 |
| DOI: | 10.32614/CRAN.package.bacistool |
| Author: | Nan Chen and J. Jack Lee |
| Maintainer: | J. Jack Lee <jjlee at mdanderson.org> |
| License: | GNU General Public License (≥ 3) |
| NeedsCompilation: | no |
| SystemRequirements: | JAGS (>= 4.3.0) |
| CRAN checks: | bacistool results |
| Reference manual: | bacistool.pdf |
| Package source: | bacistool_1.0.0.tar.gz |
| Windows binaries: | r-devel: bacistool_1.0.0.zip, r-release: bacistool_1.0.0.zip, r-oldrel: bacistool_1.0.0.zip |
| macOS binaries: | r-release (arm64): bacistool_1.0.0.tgz, r-oldrel (arm64): bacistool_1.0.0.tgz, r-release (x86_64): bacistool_1.0.0.tgz, r-oldrel (x86_64): bacistool_1.0.0.tgz |
| Old sources: | bacistool archive |
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