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.
The Rust backend requires a stable Rust toolchain with cargo and rustc.
Install one from rustup before installing this fork.
# Install coxphf from CRAN
install.packages("coxphf")
# Install the development version from GitHub
# install.packages("remotes")
remotes::install_github("carbocation/coxphf")The Rust backend is used by default. For numerical comparisons during
development, the retained reference backend can be selected with
options(coxphf.native_backend = "fortran").
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).