[R] logistic regression model with non-integer weights

[Frank E Harrell Jr]

Ramón Casero Cañas wrote:
> Frank E Harrell Jr wrote:
> 
>>This makes me think you are trying to go against maximum likelihood to
>>optimize an improper criterion.  Forcing a single cutpoint to be chosen
>>seems to be at the heart of your problem.  There's nothing wrong with
>>using probabilities and letting the utility possessor make the final
>>decision.
> 
> 
> I agree, and in fact I was thinking along those lines, but I also needed
> a way of evaluating how good is the model to discriminate between
> abnormal and normal cases, as opposed to e.g. GOF. The only way I know
> of is using area under ROC (thus setting cut-off points), which also
> followed neatly from Michael Dewey comments. Any alternatives would be
> welcome :)
> 

To get the ROC area you don't need to do any of that, and as you 
indicated, it is a good discrimination measure.  The lrm function in the 
Design package gives it to you automatically (C index), and you can also 
get it with the Hmisc package's somers2 and rcorr.cens functions.  ROC 
area is highly related to the Wilcoxon 2-sample test statistic for 
comparing cases and non-cases.

-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University