[R] How to compare areas under ROC curves calculated with ROC R package

[Tuszynski, Jaroslaw W.]

I might be missing something but I thought that AUC was a measure for
comparing ROC curves, so there is nothing else needed to "compare" them. The
larger AUC is the higher correlation of 2 variables compared. No other
measures or calculations are needed.

Jarek Tuszynski

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Laurent Fanchon
Sent: Wednesday, March 15, 2006 11:57 AM
To: r-help at stat.math.ethz.ch
Subject: [R] How to compare areas under ROC curves calculated with ROCR
package

Dear all,

I try to compare the performances of several parameters to diagnose 
lameness in dogs.
I have several ROC curves from the same dataset.
I plotted the ROC curves and calculated AUC with the ROCR package.

I would like to compare the AUC.
I used the following program I found on R-help archives :
 
From: Bernardo Rangel Tura
Date: Thu 16 Dec 2004 - 07:30:37 EST

seROC<-function(AUC,na,nn){
a<-AUC
q1<-a/(2-a)
q2<-(2*a^2)/(1+a)
se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
se
}

cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
se1<-seROC(AUC1,na1,nn1)
se2<-seROC(AUC2,na2,nn2)

sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
zad<-(AUC1-AUC2)/sed
p<-dnorm(zad)
a<-list(zad,p)
a
}

The author of this script says: "The first function (seROC) calculate the
standard error of ROC curve, the 
second function (cROC) compare ROC curves."

What do you think of this script?
Is there any function to do it better in ROCR?

Any help would be greatly appreciated. 

Laurent Fanchon
DVM, MS
Ecole Nationale Vétérinaire d'Alfort
FRANCE

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