[R] predictive accuracy

[Claudia Beleites]

Al,

I'd redo everything and report in the paper that your peculiar predictor 
was contributing strongly to models that were built without excluding 
this predictor. This is an important information: your models get 
"confused" by the predictor (I'd consider this a lack of a certain kind 
of robustness, but I'm not a statistician).

HTH

Claudia

Am 26.05.2011 14:42, schrieb El-Tahtawy, Ahmed:
> I am trying to develop a prognostic model using logistic regression.   I
> built a full , approximate models with the use of penalization - design
> package. Also, I tried Chi-square criteria, step-down techniques. Used
> BS for model validation.
>
>
>
> The main purpose is to develop a predictive model for future patient
> population.   One of the strong predictor pertains to the study design
> and would not mean much for a clinician/investigator in real clinical
> situation and have been asked to remove it.
>
>
>
> Can I propose a model and nomogram without that strong -irrelevant
> predictor?? If yes, do I need to redo model calibration, discrimination,
> validation, etc...?? or just have 5 predictors instead of 6 in the
> prognostic model??
>
>
>
> Thanks for your help
>
> Al
>
> .
>
>
>
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> 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.


-- 
Claudia Beleites
Spectroscopy/Imaging
Institute of Photonic Technology
Albert-Einstein-Str. 9
07745 Jena
Germany

email: claudia.beleites at ipht-jena.de
phone: +49 3641 206-133
fax:   +49 2641 206-399