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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 |
Author: | Samvel B. Gasparyan [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 Wins Hce maraca |
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 depends: | maraca |
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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.
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