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: | 0.6.3 |
Depends: | R (≥ 2.10) |
Imports: | base, stats |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2024-08-19 |
DOI: | 10.32614/CRAN.package.hce |
Author: | Samvel B. Gasparyan
|
Maintainer: | Samvel B. Gasparyan <gasparyan.co at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | hce results |
Reference manual: | hce.pdf |
Vignettes: |
Introduction (source, R code) Wins (source, R code) Hce (source, R code) maraca (source, R code) |
Package source: | hce_0.6.3.tar.gz |
Windows binaries: | r-devel: hce_0.6.3.zip, r-release: hce_0.6.3.zip, r-oldrel: hce_0.6.3.zip |
macOS binaries: | r-release (arm64): hce_0.6.3.tgz, r-oldrel (arm64): hce_0.6.3.tgz, r-release (x86_64): hce_0.6.3.tgz, r-oldrel (x86_64): hce_0.6.3.tgz |
Old sources: | hce archive |
Reverse depends: | maraca |
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