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The R package coxphw 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}). 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.

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Version

Install

install.packages('coxphw')

Monthly Downloads

619

Version

4.0.2

License

GPL-3

Maintainer

Daniela Dunkler

Last Published

June 22nd, 2020

Functions in coxphw (4.0.2)

PT

Pretransformation function
coxphw.control

Ancillary arguments for controling coxphw fits
biofeedback

Biofeedback Treatment Data
concord

Compute Generalized Concordance Probabilities for Objects of Class coxphw or coxph
coxphw

Weighted Estimation in Cox Regression
coxphw-package

Weighted Estimation in Cox Regression
wald

Wald-Test for Model Coefficients
vcov.coxphw

Obtain the Variance-Covariance Matrix for a Fitted Model Object of Class coxphw
gastric

Gastric Cancer Data
confint.coxphw

Confidence Intervals for Model Parameters
coef.coxphw

Extract Model Coefficients for Objects of Class coxphw
fp.power

Provides Fractional Polynomials as Accessible Function
summary.coxphw

Summary Method for Objects of Class coxphw
plot.coxphw

Plot Weights of Weighted Estimation in Cox Regression
print.coxphw.predict

Print Method for Objects of Class predict.coxphw
predict.coxphw

Predictions for a weigthed Cox model
print.coxphw

Print Method for Objects of Class coxphw
plot.coxphw.predict

Plot the Relative or Log Relative Hazard Versus Values of a Continuous Covariable.