RABR: Simulations for Response Adaptive Block Randomization Design

Conduct simulations of the Response Adaptive Block Randomization (RABR) design to evaluate its type I error rate, power and operating characteristics for binary and continuous endpoints. For more details of the proposed method, please refer to Zhan et al. (2021) <doi:10.1002/sim.9104>.

Version: 0.1.1
Imports: asd, cubature, data.table, doParallel, foreach, ggplot2, multcomp, multxpert, parallel, survival
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0)
Published: 2022-08-17
DOI: 10.32614/CRAN.package.RABR
Author: Tianyu Zhan ORCID iD [aut, cre]
Maintainer: Tianyu Zhan <tianyu.zhan.stats at gmail.com>
BugReports: https://github.com/tian-yu-zhan/RABR/issues
License: MIT + file LICENSE
URL: https://github.com/tian-yu-zhan/RABR
NeedsCompilation: no
Materials: README, NEWS
In views: ClinicalTrials
CRAN checks: RABR results

Documentation:

Reference manual: RABR.html , RABR.pdf
Vignettes: RABR-vignette (source, R code)

Downloads:

Package source: RABR_0.1.1.tar.gz
Windows binaries: r-devel: RABR_0.1.1.zip, r-release: RABR_0.1.1.zip, r-oldrel: RABR_0.1.1.zip
macOS binaries: r-release (arm64): RABR_0.1.1.tgz, r-oldrel (arm64): RABR_0.1.1.tgz, r-release (x86_64): RABR_0.1.1.tgz, r-oldrel (x86_64): RABR_0.1.1.tgz
Old sources: RABR archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RABR to link to this page.