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
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