Re: st: Logit and percentage of correct classification

[Fred Wolfe <fwolfe@arthritis-research.org>]

In addition to Ronan's important point, another point that might be made is 
that model performance as assessed by simple logistic regression is overly 
optimistic. Running the model with 10-fold cross validation (as may be 
obtained in CART or by programming in Stata) is often illuminating as to 
the truer predictive ability of models.

Fred Wolfe

At 04:48 AM 9/3/2004, you wrote:

> Herve STOLOWY wrote:
>
> > Dear All:
> > Is there an easy way to determine the percentage of correct
> > classification (predicted probabilities) after a logit (or logistic)
> > regression (equivalent to Predicted/Percentage correct in SPSS)?
> You can, using -predict-, generate the predicted probability. You can then 
> decide on an appropriate threshold for a predicted event. The usual one is 
> 0.5, but there are many situations where the consequences of incorrect 
> prediction are quite different for false positive and false negative 
> predictions.
>
> For instance, the current European guidelines for prevention of 
> cardiovascular disease recommend treatment when a person has a 10% chance 
> of a fatal heart attack or stroke. Except, of course, for the British, who 
> use a threshold of 30% risk of fatal or non-fatal heart attack. The 
> cutpoints at which you evaluate your model fit need to be established 
> pragmatically.
>
> You can then assess your model performance using -diagt-, which gives 
> detailed statistics on the pattern of errors in your prediction system.
>
>
>
> Ronan M Conroy (rconroy@rcsi.ie)
> Senior Lecturer in Biostatistics
> Royal College of Surgeons
> Dublin 2, Ireland
> +353 1 402 2431 (fax 2764)
> --------------------
> Just say no to drug reps
> http://www.nofreelunch.org/
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Fred Wolfe
National Data Bank for Rheumatic Diseases
Wichita, Kansas
Tel (316) 263-2125     Fax (316) 263-0761
fwolfe@arthritis-research.org


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