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Here is an example of how to do it. > library(survival) > vfit <- coxph(Surv(time, status) ~ celltype + trt, data=veteran) > userinput <- data.frame(celltype="smallcell", trt = 1) > usercurve <- survfit(vfit, newdata=userinput) #the entire predicted survival curve > user2 <- summary(usercurve, time= 2*365.25) # 2 year time point > user2$surv [1] 0.0007438084 Some comments: 1. The summary function for survival curves was written so t...

...(veteran,Surv(time,status)) vetcoxph=coxph(obj~celltype+trt,data=veteran) #I will fit models from both the survival and rms packages so you can #use what you like vetcph=cph(obj~celltype+trt,data=veteran,surv=TRUE,time.inc=5*365,x=T,y=T) #let's say the user inputted that their cell type was smallcell and their treatment was "1". userinput=data.frame(celltype='smallcell',trt=factor(1)) I really appreciate your recommendations Best, Jahan -- View this message in context: http://r.789695.n4.nabble.com/Building-a-web-risk-calculator-based-on-Cox-PH-definitive-method-for-cal...