[R] Logistic Regression - Interpreting SENS (Sensitivity) and SPEC (Specificity)

Frank E Harrell Jr f.harrell at vanderbilt.edu
Mon Oct 13 18:26:26 CEST 2008

Dieter Menne wrote:
> Maithili Shiva <maithili_shiva <at> yahoo.com> writes:
>> I havd main sample of 42500 clentes and
>> based on their status as regards to defaulted / non - defaulted, I have
> genereted the probability of default.
>> I have a hold out sample of 5000 clients. I have calculated (1) No of
> correctly classified goods Gg, (2) No of
>> correcly classified Bads Bg and also (3) number of wrongly classified bads
> (Gb) and (4) number of wrongly
>> classified goods (Bg).
> The simple and wrong answer is to use these data directly to compute sensitivity
> (fraction of hits). This measure is useless, but I encounter it often in medical
> publications.

Exactly.  Using classification accuracy, sensitivity, specificity means 
that you are not using the model's predicted probabilities in a 
reasonable or powerful way.  Credit scoring models need to demonstrate 
absolute calibration accuracy.


> You can get a more reasonable answer by using cross-validation. Check, for
> example, Frank Harrell's 
> http://biostat.mc.vanderbilt.edu/twiki/pub/Main/RmS/logistic.val.pdf
> Dieter
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Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

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