Tuszynski, Jaroslaw W. wrote: > 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
A single AUC does not compare two competing predictors; it only measures the predictive discrimination of a single predictor (or a single model). Note that testing for differences in ROC areas results in a test with low power. There are much more powerful approaches such as likelihood ratio chi-square tests for embedded models. The code you included below seems to make some strong assumptions about how AUC is estimated. Nonparametric AUC estimators (related to the Wilcoxon test, for example, which is a preferred method) do not have simple formulas for standard errors. Frank Harrell > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Laurent Fanchon > Sent: Wednesday, March 15, 2006 11:57 AM > To: [email protected] > 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 > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
