hce: Design and Analysis of Hierarchical Composite Endpoints

Simulate and analyze hierarchical composite endpoints. Win odds is the main analysis method, but other win statistics (win ratio, net benefit) are implemented as well in case of no censoring. See Gasparyan SB et al (2023) "Hierarchical Composite Endpoints in COVID-19: The DARE-19 Trial." Case Studies in Innovative Clinical Trials, 95-148. Chapman; Hall/CRC. <doi:10.1201/9781003288640-7>.

Version: 0.6.0
Depends: R (≥ 2.10)
Imports: base, stats
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-03-12
DOI: 10.32614/CRAN.package.hce
Author: Samvel B. Gasparyan ORCID iD [aut, cre]
Maintainer: Samvel B. Gasparyan <gasparyan.co at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: hce results


Reference manual: hce.pdf
Vignettes: Introduction


Package source: hce_0.6.0.tar.gz
Windows binaries: r-devel: hce_0.6.0.zip, r-release: hce_0.6.0.zip, r-oldrel: hce_0.6.0.zip
macOS binaries: r-release (arm64): hce_0.6.0.tgz, r-oldrel (arm64): hce_0.6.0.tgz, r-release (x86_64): hce_0.6.0.tgz, r-oldrel (x86_64): hce_0.6.0.tgz
Old sources: hce archive

Reverse dependencies:

Reverse depends: maraca


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