Hi,
I just started learning R to do survival analysis using coxphfit and survfit (to compare to neural network prediction for survival).  Currently, I can generate the Cox model using N cases and then get the estimated survival times for the same N cases with survfit.cox <- coxph(Surv(time,delta)~X1+X2+X3)
tmp <- data.frame(X1,X2,X3)
sf <- survfit(coxfit,newdata=tmp)My question is if it's possible to perform cross-validation with the Cox model, i.e. if I have N cases, can I fit the Cox model to N-1 cases (i.e. generate beta coefficients) and then test the model on the Nth case to see the estimated survival?  This is what I do with neural networks.
Thank you for your help!
~Neha


      
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