[R] Fw: Logistic regresion - Interpreting (SENS) and (SPEC)

[Frank E Harrell Jr]

Maithili Shiva wrote:
> Dear Mr Peter Dalgaard and Mr Dieter Menne,
> 
> I sincerely thank you for helping me out with my problem. The thing is taht I already have calculated SENS = Gg / (Gg + Bg) = 89.97%
> and SPEC = Bb / (Bb + Gb) = 74.38%.
> 
> Now I have values of SENS and SPEC, which are absolute in nature. My question was how do I interpret these absolue values. How does these values help me to find out wheher my model is good.
> 
> With regards
> 
> Ms Maithili Shiva

I can't understand why you are interested in probabilities that are in 
backwards time order.

Frank

> 
> ________________________________________________________________________
> 
> 
> 
> 
> 
> 
>> Subject: [R] Logistic regresion - Interpreting (SENS) and (SPEC)
>> To: r-help at r-project.org
>> Date: Friday, October 10, 2008, 5:54 AM
>> Hi
>>
>> Hi I am working on credit scoring model using logistic
>> regression. 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).
>>
>> My prolem is how to interpret these results? What I have
>> arrived at are the absolute figures.
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained,
>> reproducible code.
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 


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