Package: coxphw 4.0.3

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]

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coxphw/json (API)
NEWS

# Install 'coxphw' in R:
install.packages('coxphw', repos = c('https://biometrician.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:

On CRAN:

cox-regressionsurvival-analysis

6 exports 1 stars 2.33 score 3 dependencies 1 dependents 7 mentions 27 scripts 508 downloads

Last updated 10 months agofrom:3efc7cad73. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 01 2024
R-4.5-win-x86_64OKSep 01 2024
R-4.5-linux-x86_64OKSep 01 2024
R-4.4-win-x86_64OKSep 01 2024
R-4.4-mac-x86_64OKSep 01 2024
R-4.4-mac-aarch64OKSep 01 2024
R-4.3-win-x86_64OKSep 01 2024
R-4.3-mac-x86_64OKSep 01 2024
R-4.3-mac-aarch64OKSep 01 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 Sep 01 2024.

Last update: 2020-06-16
Started: 2020-06-16