Dear R-helper,
I am trying to compare two AUCs derived from same population, but one
is derived by adding extra features on top of the other. I found the
codes below from R-help. I would like to know, in my case, whether I
could use cROC, and also how can I got the right correlation (r)?
I have been back to the original paper(Hanley 1983). It suggested to
calculate rN(correlation coefficient for the discriminant value for +1
labeled value) and rA(correlation coefficient for the discriminant
value for -1 labeled value) and then calculate the average correlation
and look up the Table they provided (row: average correlation, column:
average AUC). However, in that Table the Average AUC need to be bigger
than 0.70, which limits the search (always need to have average AUC
larger than 0.70). Would you please suggested some way to calculate
the correlation ?
Thank you very much!
Cheers,
Xiao
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
}