Hi Lars, Graph it:
plot(pred_leuk) will show that some of the survival curves do not reach 0.5 before you run out of data. Thus the median is not estimated and you get NA. Chris -----Original Message----- From: Lars Bishop [mailto:lars...@gmail.com] Sent: Thursday, July 10, 2014 6:23 AM To: r-help@r-project.org Subject: [R] Median expected survival Hi All, Apologies for the simple question, but I could not find a straightforward answer based on my limited knowledge of survival analysis. I’m trying to obtain the predicted median survival time for each subject on a new dataset from a fitted coxph{survival} or cph{rms} object. Would the quantile.survfit function (as used below) return the expected median survival? Why this function returns NAs in this case, when all predictors have non-missing values? As an alternative, I’ve tried to use the Quntile{rms} function as in my second chunk of code, but in this case I get an error message (most likely due to my lack of understanding as well). library(MASS) library(survival) library(rms) data(gehan) leuk.cox <-coxph(Surv(time, cens) ~ treat + factor(pair), data = gehan) leuk_new <- gehan[1:10, ] # take first 10 patients pred_leuk <- survfit(leuk.cox, newdata=leuk_new) quantile(pred_leuk, 0.5)$quantile ### alternative using rms leuk.cox.rms <-cph(Surv(time, cens) ~ treat + factor(pair), data = gehan, surv = T) med <- Quantile(leuk.cox.rms) Predict(leuk.cox.rms, data = leuk_new, fun=function(x)med(lp=x)) >Error in Predict(leuk.cox.rms, data = leuk_new, fun = function(x) med(lp = x)) : predictors(s) not in model: data Thank you for your help. Best, Lars. [[alternative HTML version deleted]] ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues ______________________________________________ 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.
