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:Daniela Dunkler [aut, cre], Georg Heinze [aut], Meinhard Ploner [aut]

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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/biometrician/coxphw/issues

Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:

4.45 score 1 stars 1 packages 27 scripts 470 downloads 7 mentions 6 exports 3 dependencies

Last updated 1 years agofrom:db21b7512c. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-linux-x86_64OKNov 23 2024

Exports:concordcoxphwcoxphw.controlfp.powerPTwald

Dependencies:latticeMatrixsurvival

R code for 'Weighted Cox Regression using the R package coxphw'

Rendered fromjss_2018_example_code.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2020-06-22
Started: 2018-04-17