coxphw: Weighted Estimation in Cox Regression

Implements weighted estimation in Cox regression as proposed by Schemper, Wakounig and Heinze (Statistics in Medicine, 2009, <doi:10.1002/sim.3623>) and as described in Dunkler, Ploner, Schemper and Heinze (Journal of Statistical Software, 2018, <doi:10.18637/jss.v084.i02>). Weighted Cox regression provides unbiased average hazard ratio estimates also in case of non-proportional hazards. Approximated generalized concordance probability an effect size measure for clear-cut decisions can be obtained. The package provides options to estimate time-dependent effects conveniently by including interactions of covariates with arbitrary functions of time, with or without making use of the weighting option.

Version: 4.0.3
Depends: R (≥ 3.0.2), survival
Suggests: knitr, rmarkdown, testthat
Published: 2023-11-28
Author: Daniela Dunkler [aut, cre], Georg Heinze [aut], Meinhard Ploner [aut]
Maintainer: Daniela Dunkler <daniela.dunkler at meduniwien.ac.at>
BugReports: https://github.com/biometrician/coxphw/issues
License: GPL-3
URL: https://github.com/biometrician/coxphw
NeedsCompilation: yes
Citation: coxphw citation info
Materials: README NEWS
In views: Survival
CRAN checks: coxphw results

Documentation:

Reference manual: coxphw.pdf
Vignettes: R code for 'Weighted Cox Regression using the R package coxphw'

Downloads:

Package source: coxphw_4.0.3.tar.gz
Windows binaries: r-devel: coxphw_4.0.3.zip, r-release: coxphw_4.0.3.zip, r-oldrel: coxphw_4.0.3.zip
macOS binaries: r-release (arm64): coxphw_4.0.3.tgz, r-oldrel (arm64): coxphw_4.0.3.tgz, r-release (x86_64): coxphw_4.0.3.tgz
Old sources: coxphw archive

Reverse dependencies:

Reverse suggests: simIDM

Linking:

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