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BayesDIP: Bayesian Decreasingly Informative Priors for Early Termination Phase II Trials
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>.
Getting started
Browse package contents
Package details |
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| Author | Chen Wang [cre, aut], Roy Sabo [aut] |
| Maintainer | Chen Wang <wangc10@vcu.edu> |
| License | GPL (>= 2) |
| Version | 0.1.1 |
| URL | <https://github.com/chenw10/BayesDIP> |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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