# Discrimination and calibration of Cox model

I have been working on fitting Cox model for prediction by using the rms package. I want to measure model calibration and discrimination. Discrimination was measured by using rms::validate(); Dxy can be transferred to @Frank Harrell's $c$ index. But in this way, I cannot get 95% CI for the $c$ index. How can I do this in R? And by the way, what value should be in $c$ index to present the model's well?

Calibration was done using rms::calibrate(), but I cannot get the calibration plot which presented concordance of predicted and observed events in Cox model. How can I do this calibration plot of Cox model in R or SAS.

• Note that if you ever need to do out-of-sample (external) validation, the rcorr.cens function in the R Hmisc package provides the standard error of Somers' $D_{xy}$ which gives rise to a confidence interval that can be translated to an interval for $c$. But for internal validation we don't at present have a standard error for $D_{xy}$. Apr 29 '12 at 12:26