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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 also implemented, provided there is 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: 0.6.5
Depends: R (≥ 2.10)
Imports: base, stats
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-10-16
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 NEWS
CRAN checks: hce results

Documentation:

Reference manual: hce.pdf
Vignettes: Introduction (source, R code)
Wins (source, R code)
Hce (source, R code)
maraca (source, R code)

Downloads:

Package source: hce_0.6.5.tar.gz
Windows binaries: r-devel: hce_0.6.5.zip, r-release: hce_0.6.5.zip, r-oldrel: hce_0.6.5.zip
macOS binaries: r-release (arm64): hce_0.6.5.tgz, r-oldrel (arm64): hce_0.6.5.tgz, r-release (x86_64): hce_0.6.5.tgz, r-oldrel (x86_64): hce_0.6.5.tgz
Old sources: hce archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.