I am fitting a coxph model on a large dataset (approx 100,000 patients), and then trying to estimate the survival curves for several new patients based on the coxph object using survfit. When I run coxph I get the coxph object back fairly quickly however when I try to run survfit it does not come back. I am wondering if their is a more efficient way to get predicted survival curves from a coxph object.predict.coxph does not seem to generate survival curves.
here is some sample code that mirrors what I am trying to do with my dataset, I get results using this code but it still takes a long time, my dataset includes quite a few more covariates, so any suggestions on speeding this up would be greatly appreciated. library(survival) ### generate sample data time <- rexp(100000,(1/180)) ag <- rnorm(100000,38,12) sx <- sample(x=c(0,1),100000,replace=TRUE) ac <- factor(sample(x=c(1,2,3,4,5),100000,replace=TRUE),levels=c(1:5)) ev <- sample(x=c(0,1),100000,replace=TRUE) c1 <- as.data.frame(cbind(ag,sx,ac)) #generate newdata ts <- as.data.frame (cbind(ag[23:24],sx[1000:1001],factor(ac[9000:9001],levels=c(1:5)))) colnames(ts) <- c("ag","sx","ac") cph <- coxph(Surv(time,ev)~ ag+sx+ac,data=c1) survfit(cph,newdata=ts,individual=F) thanks, Spencer [[alternative HTML version deleted]] ______________________________________________ R-help@stat.math.ethz.ch 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.