Computing Confidence Intervals for AUC in ROCR Package

Dear R-philes,

I am plotting ROC curves for several cross-validation runs of a  
classifier (using the function below).  In addition to the average  
AUC, I am interested in obtaining a confidence interval for the  
average AUC.  Is there a straightforward way to do this via the ROCR  
package?
You should probably contact the authors. When I tried using that  
package a few weeks ago, several of the annotation features were  
broken. I contacted the author who said there had been problems after  
converting to S4 method. He also said there would be a fix but not  
immediately. There has been a release since that time and I tried it,   
but it did not appear to fix the problems I encountered. All I was  
able to get were very simple ROC curves without any confidence  
intervals or marking of levels. I ended up turning to the Epi package  
for what I needed ( but I did not need confidence intervals so cannot  
comment on that aspect.)
David.

>
> plot_roc_curve <- function(roc.dat, plt.title) {
> 	#print(str(vowel.ROC))
> 	pred <- prediction(roc.dat$predictions, roc.dat$labels)
> 	perf <- performance(pred, "tpr", "fpr")
> 	perf.auc <- performance(pred, "auc")
> 	perf.auc.areas <- slot(perf.auc, "y.values")
> 	curve.area <- mean(unlist(perf.auc.areas))
> 	#quartz(width=4, height=6)
> 	plot(perf, col="grey82", lty=3)
> 	plot(perf,lwd=3,avg="horizontal",spread.estimate="boxplot",
> 		add=T)
> 	title(main=plt.title)
> 	mtext(sprintf("%s%1.4f", "Area under Curve = ", curve.area),
> 		side=3, line=0, cex=0.8)
> }
>
> P.S. After years of studying statistical analysis as a student, I  
> still consider myself a novice.
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

David Winsemius, MD
Heritage Laboratories
West Hartford, CT

Computing Confidence Intervals for AUC in ROCR Package

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