>I'm working on Proc Logistic and have a question about the AIC statistic
>versus the c statistic.
>I did take the SAS Categorical Data Analysis class, and was taught there to
>look for the smallest AIC statistic, and the largest c statistic.
But you can't count on them to agree. Even if you focus on, say, two
similar measures which address the same thing, say AIC and SBC (both of
which look at information theoretic concepts), you cannot count on both
of them giving you the same model.
>I'm now comparing two models:
>1. AIC= 983.21, c statistic= .74
>2. AIC= 940.17, c statistic= .757
Here, the models are so close that if you plotted these with your other
model results that you might not be able to tell which was better from
>Model 2 has the same variables as model 1, with one additional variable,
>whose type 3 effect is significant at .01.
>My question is, why don't I see a bigger jump in the c statistic (about a
>2% rise) when the AIC statisitic is dropping substantially (about a 5%
I don't see a big change in either. I would personally say that either
would be an acceptable choice, given these results, so I would pick the
one that makes more sense from a subject matter POV.
But first I would check things like missing values (to see if one
is driven by changes in the number of records used), and diagnostic plots
see if there are problems that I need to address before I consider showing
either model to anyone). I'm Obsessive-Compulsive like that. :-)
David L. Cassell
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