Dear all
I am trying to compare the performances of several methods using the AUC0.1
and
not the whole AUC. (meaning I wanted to compare to AUC's whose x axis only
goes to
0.1 not 1)
I came to know about the Mcneil Hanley test from Bernardo Rangel Tura
and I referred to the original paper for the calculation of "r" which is an
argument of the function
cROC. I can only find the value of "r" for the whole AUC's .
> 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
Could somebody kindly suggest me how to calculate the value of "r" or
some ways to calculate the statistical significance measure for the
differences of auc for a part of
the curve like AUC0.1.
Thank You
--
Dukka KC
UNCC
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