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05-10-2017 06:04 AM - edited 05-10-2017 06:25 AM

Hi all,

i want to make a ROC curve for an hold out sample. The thing is, i made a logistic regression for some data i have from the year 2007 and I want to see how this model fits the data in the year 2008. I can't use this code:

proc logistic data = sasdata.Data2008;

model flag(event='1')=TL_TA EAT_TA AGE /outroc=r;

run;

because then my model and my ROC curve is based on a logistic regression on the 2008 dataset. I want to do a logistc regression on the 2007 set, and then use this fit to see how it fits the 2008 data set. So i tried this:

proc logistic data=sasdata.data2007;

class AGE (ref='Ny') / param = ref;

model flag(event="1") = TL_TA EAT_TA AGE / CTABLE outroc=troc;

score data=sasdata.data2008 out=valpred outroc=vroc;

roc; roccontrast;

run;

This seems ok. I get a ROC curve both for the fit of 2007 and then a ROC curve for how the 2007 model fits on the 2008 model. The thing is, i want to find the optimale cutoff point in 2008, where the euclidean distance from 1.0 is minimized to the ROC curve, how can i do that? The ctable option gives me the predicted probabilities for the 2007 data set only.

I hope you can help.

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05-11-2017 10:22 AM

See the ROCPLOT macro. Specify the SCORE OUTROC= data set in the INROC= macro option, and the SCORE OUT= data set and its predicted probabilities in the macro's INPRED= and P= options. See the macro documentation for information on the various optimality criteria you can use.