Weighted Estimation in Cox Regression

Implements weighted estimation in Cox regression as proposed by Schemper, Wakounig and Heinze (Statistics in Medicine, 2009, ) and as described in Dunkler, Ploner, Schemper and Heinze (Journal of Statistical Software, 2018, ). 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.

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.