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- ROC in PROC LOGISTIC using weights

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08-15-2011 05:04 PM

Hi all -

I have run a PROC LOGISTIC with and without my weight variable. The regression seems fine and agrees SPSS and Stata where I specified the same model. More of hte predictors are signifigant for the weighted data, and the overall R2 is higher. (I did have to tell SAS to model event=1 to get the same outputs.) However, the area under the ROC curve gets smaller in SAS weighted model, where it should be increasing. It increases when I produce ROC after weighted logistic in Stata, and when ROC curves are obtained in SPSS.

It almost looks like the ROC plot is not using the weights - except the area under the curve is even smaller than the ROC area form theunweighted analysis.

I am going to try generating a score dataset, and computing the sensitivity and susceptibility to do my own ROC calculations - but I though I would ask if anyone else has seen this.

Thanks

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08-15-2011
07:37 PM

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08-15-2011 07:37 PM

By default, weights are used to fit the model, but not to compute the ROC. See if the ROCOPTIONS(WEIGHTED) option on the PROC LOGISTIC statement addresses your needs.

Rick

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08-15-2011
07:37 PM

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08-15-2011 07:37 PM

By default, weights are used to fit the model, but not to compute the ROC. See if the ROCOPTIONS(WEIGHTED) option on the PROC LOGISTIC statement addresses your needs.

Rick

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08-16-2011 10:01 AM

This worked perfectly. However, it begs the question, "Why is this the default?". In other words, what is the value of ROC and AUC without weights when weights have been used? IS there some downside or bias to the weighted ROC?