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>.

Version:	0.1.1
Imports:	stats
Published:	2023-02-02
DOI:	10.32614/CRAN.package.BayesDIP
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

Documentation:

Reference manual:

BayesDIP.html , BayesDIP.pdf

Downloads:

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

Linking:

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