coxphfplot(formula = attr(data, "formula"), data = sys.parent(), profile, pitch = 0.05, limits, alpha = 0.05, maxit = 50, maxhs = 5, epsilon = 1e-06, maxstep = 2.5, firth = TRUE, legend = "center", ...)~ A or ~ A : C.maxhs halvings.firth=TRUE, default) or the
standard maximum likelihood method (firth=FALSE) for fitting the Cox model.xHeinze G and Schemper M (2001). A Solution to the Problem of Monotone Likelihood in Cox Regression. Biometrics 57(1):114--119.
Heinze G (1999). Technical Report 10/1999: The application of Firth's procedure to Cox and logistic regression. Section of Clinical Biometrics, Department of Medical Computer Sciences, University of Vienna, Vienna. http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/statistical-software/fccoxphf/ Heinze G and Ploner M (2002). SAS and SPLUS programs to perform Cox regression without convergence problems. Computer Methods and Programs in Biomedicine 67:217-223
time<-c(1,2,3)
cens<-c(1,1,1)
x<-c(1,1,0)
sim<-cbind(time,cens,x)
sim<-data.frame(sim)
profplot<-coxphfplot(sim, formula=Surv(time,cens)~x, profile=~x)
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