Hi Group,
I have a question about obtaining the bias-corrected c-index using
validate from the Design library.
As an example, consider the example from help page:
library(Design)
?validate.lrm
n <- 1000
age <- rnorm(n, 50, 10)
blood.pressure <- rnorm(n, 120, 15)
cholesterol <- rnorm(n, 200, 25)
sex <- factor(sample(c('female','male'), n,TRUE))
L <- .4*(sex=='male') + .045*(age-50) + (log(cholesterol -
10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
y <- ifelse(runif(n) < plogis(L), 1, 0)
f <- lrm(y ~ sex*rcs(cholesterol)+pol(age,2)+blood.pressure, x=TRUE, y=TRUE)
validate(f, B=100)
The output does not include c, but it does include Dxy. The bias
corrected Dxy = 0.280.
Is it correct for me to say that the bias corrected c-index is:
0.280/2 + 0.5 = 0.64?
Also, I have seen this described as the c-index, which is a
generalization of the c-statistic. Is there
a difference? I thought both of these quantities refer to the area
under the ROC.
Thanks!
Juliet
______________________________________________
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.
