Package: BayesDIP 0.1.1

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>.

Authors:Chen Wang [cre, aut], Roy Sabo [aut]

BayesDIP_0.1.1.tar.gz
BayesDIP_0.1.1.zip(r-4.5)BayesDIP_0.1.1.zip(r-4.4)BayesDIP_0.1.1.zip(r-4.3)
BayesDIP_0.1.1.tgz(r-4.4-any)BayesDIP_0.1.1.tgz(r-4.3-any)
BayesDIP_0.1.1.tar.gz(r-4.5-noble)BayesDIP_0.1.1.tar.gz(r-4.4-noble)
BayesDIP_0.1.1.tgz(r-4.4-emscripten)BayesDIP_0.1.1.tgz(r-4.3-emscripten)
BayesDIP.pdf |BayesDIP.html
BayesDIP/json (API)
NEWS

# Install 'BayesDIP' in R:
install.packages('BayesDIP', repos = c('https://chenw10.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/chenw10/bayesdip/issues

On CRAN:

2.70 score 1 scripts 639 downloads 10 exports 0 dependencies

Last updated 2 years agofrom:fa91ebb189. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-winOKNov 18 2024
R-4.5-linuxOKNov 18 2024
R-4.4-winOKNov 18 2024
R-4.4-macOKNov 18 2024
R-4.3-winOKNov 18 2024
R-4.3-macOKNov 18 2024

Exports:OneSampleBernoulliOneSampleBernoulli.DesignOneSampleNormal1OneSampleNormal1.DesignOneSampleNormal2OneSampleNormal2.DesignOneSamplePoissonOneSamplePoisson.DesignTwoSampleBernoulliTwoSampleBernoulli.Design

Dependencies: