The version 1.2 of pROC has just been released.

The main feature of this new version: the confidence interval of an AUC can be computed with the DeLong¹ method.

library(pROC)
data(aSAH)
rocs100 <- roc(aSAH$outcome, aSAH$s100)
ci(rocs100)

Obviously they can still be computed with bootstrap:

ci(rocs100, method="bootstrap")

But the DeLong method is significantly faster. It works on full AUC only – for partial AUC you still have the bootstrap only.

Here is the full change log:

• Added DeLong method in ci.auc (with a GUI, S+ only).
• Return value of ci.auc does not contain an "aucs" item anymore.
• Put most examples with bootstrap within \dontrun{} blocks for faster (but less useful) checks execution.

You can find the new version on ExPASy and on the CRAN. To update, type update.packages() or install.packages("pROC") if you want to update pROC only.

• 1. Elisabeth R. DeLong, David M. DeLong and Daniel L. Clarke-Pearson (1988) “Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach”. Biometrics 44, 837–845.