Michal Figurski wrote:
Dear R-Helpers,
I am a novice in survival analysis. I have the following code:
for (i in 3:12) print(coxph(Surv(time, status)~a[,i], data=a))
I used it to fit the Cox Proportional Hazard models separately for every
available parameter (columns 3:12) in my data set - with intention to
compare the Hazard Ratios.
However, some of my variables are in range 0.1 to 1.6, others in range
5000 to 9000. How do I compare HRs between such variables?
I have rescaled all the variables to be in 0 to 1 range - is this the
proper way to go? Is there a way to somehow calculate the same HRs (as
for rescaled parameters) from the HRs for original parameters?
Many thanks in advance.
There are a lot of issues related to this that will require a good bit
of study, both in survival analysis and in regression. I would start
with bootstrapping the ranks of the likelihood ratio chi-square
statistics of the competing biomarkers.
Frank
--
Frank E Harrell Jr Professor and Chairman School of Medicine
Department of Biostatistics Vanderbilt University
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
