Package: coxphw 4.0.3
Daniela Dunkler
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.
Authors:
coxphw_4.0.3.tar.gz
coxphw_4.0.3.tar.gz(r-4.5-noble)coxphw_4.0.3.tar.gz(r-4.4-noble)
coxphw_4.0.3.tgz(r-4.4-emscripten)coxphw_4.0.3.tgz(r-4.3-emscripten)
coxphw.pdf |coxphw.html✨
coxphw/json (API)
NEWS
| # Install 'coxphw' in R: |
| install.packages('coxphw', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/biometrician/coxphw/issues3 issues
- biofeedback - Biofeedback Treatment Data
- gastric - Gastric Cancer Data
Last updated 1 years agofrom:db21b7512c. Checks:3 OK. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 23 2025 |
| R-4.5-linux-x86_64 | OK | Mar 23 2025 |
| R-4.4-linux-x86_64 | OK | Mar 23 2025 |
Citation
To cite coxphw in publications use:
Dunkler D, Ploner M, Schemper M, Heinze G (2018). “Weighted Cox Regression Using the R Package coxphw.” Journal of Statistical Software, 84(2), 1–26. doi:10.18637/jss.v084.i02.
Corresponding BibTeX entry:
@Article{,
title = {Weighted Cox Regression Using the {R} Package {coxphw}},
author = {Daniela Dunkler and Meinhard Ploner and Michael Schemper
and Georg Heinze},
journal = {Journal of Statistical Software},
year = {2018},
volume = {84},
number = {2},
pages = {1--26},
doi = {10.18637/jss.v084.i02},
}
Readme and manuals
The R package coxphw implements weighted estimation in Cox regression as proposed by Schemper, Wakounig and Heinze (Statistics in Medicine, 2009, https://doi.org/10.1002/sim.3623) and as described in Dunkler, Ploner, Schemper and Heinze (Journal of Statistical Software, 2018, https://doi.org/10.18637/jss.v084.i02). 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.
This package is licensed under GPL-3, and available on CRAN: https://cran.r-project.org/package=coxphw.
