Confidence intervals for bootstrap-validated bias-corrected performance estimates

Try this out - simple case of just getting a rough confidence interval for Dxy.

require(rms)
B <- 250; reps <- 500; dxy <- numeric(reps)  
n <- nrow(d)
f <- lrm(y ~ x1 + x2 + x3 + ..., data=d, x=TRUE, y=TRUE)
f    # show original model fit
validate(f, B=B)    # show overall validation
for(i in 1 : reps) {
   g <- update(f, subset=sample(1 : n, n, replace=TRUE))
   v <- validate(g, B=B)
   dxy[i] <- v['Dxy', 'index.corrected']
   }
quantile(dxy, c(.025, .975))
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