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Provide early termination phase II trial designs with a decreasingly informative prior (DIP) or a regular Bayesian prior chosen by the user. The program can determine the minimum planned sample size necessary to achieve the user-specified admissible designs. The program can also perform power and expected sample size calculations for the tests in early termination Phase II trials. See Wang C and Sabo RT (2022) <doi:10.18203/2349-3259.ijct20221110>; Sabo RT (2014) <doi:10.1080/10543406.2014.888441>.
| Version: | 0.1.1 |
| Imports: | stats |
| Published: | 2023-02-02 |
| Author: | Chen Wang [cre, aut], Roy Sabo [aut] |
| Maintainer: | Chen Wang <wangc10 at vcu.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | <https://github.com/chenw10/BayesDIP> |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | README NEWS |
| CRAN checks: | BayesDIP results |
| Reference manual: | BayesDIP.pdf |
| Package source: | BayesDIP_0.1.1.tar.gz |
| Windows binaries: | r-devel: BayesDIP_0.1.1.zip, r-release: BayesDIP_0.1.1.zip, r-oldrel: BayesDIP_0.1.1.zip |
| macOS binaries: | r-release (arm64): BayesDIP_0.1.1.tgz, r-oldrel (arm64): BayesDIP_0.1.1.tgz, r-release (x86_64): BayesDIP_0.1.1.tgz, r-oldrel (x86_64): BayesDIP_0.1.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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