Hello, Then the C-stat from the model is different from the computed one using rcorr.cens library(rms) n <- 1000 set.seed(17) age <- rnorm(n, 50, 10) blood.pressure <- rnorm(n, 120, 15) cholesterol <- rnorm(n, 200, 25) sex <- factor(sample(c('female','male'), n,TRUE)) ch <- cut2(cholesterol, g=40, levels.mean=TRUE) # use mean values in intervals modx <- lrm(ch ~ age) NewDat <- data.frame(age) c(modx$stats["C"], rcorr.cens(predict(modx,newdata=NewDat), ch)["C Index"], rcorr.cens(predict(modx,newdata=NewDat,type="fitted")[,1], ch)["C Index"], rcorr.cens(predict(modx,newdata=NewDat,type="fitted")[,2], ch)["C Index"]) Many Thanks Linda [[alternative HTML version deleted]]