Implements Firth's penalized maximum likelihood bias reduction method for Cox regression which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function), see Heinze and Schemper (2001) and Heinze and Dunkler (2008). The program fits profile penalized likelihood confidence intervals which were proved to outperform Wald confidence intervals.
The package coxphf implements Firth's penalized maximum likelihood bias reduction method for Cox regression which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function). The program fits profile penalized likelihood confidence intervals which were proved to outperform Wald confidence intervals.
# Install coxphf from CRAN
install.packages("coxphf")
# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("georgheinze/coxphf")
The call of the main function of the library follows the structure of the standard functions requiring a data.frame and a formula for the model specification. The response must be a survival object as returned by the 'Surv' function (see its documentation in the survival package). The resulting object belongs to the new class coxphf.
library(survival)
data(breast)
fit.breast<-coxphf(data=breast, Surv(TIME,CENS)~T+N+G+CD)
summary(fit.breast)
This work was supported by the Austrian Science Fund (FWF) (award I 2276).