On May 26, 2011, at 7:42 AM, El-Tahtawy, Ahmed wrote:

> 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


Is it that the study design characteristic would not make sense to a clinician 
but is relevant to future samples, or that the study design characteristic is 
unique to the sample upon which the model was developed and is not relevant to 
future samples because they will not be in the same or a similar study?

Is the study design characteristic a surrogate for other factors that would be 
relevant to future samples? If so, you might engage in a conversation with the 
clinicians to gain some insights into other variables to consider for inclusion 
in the model, that might in turn, help to explain the effect of the study 
design variable.

Either way, if the covariate is removed, you of course need to engage in fully 
re-evaluating the model. You cannot just drop the covariate and continue to use 
model fit assessments made on the full model.

HTH,

Marc Schwartz

______________________________________________
R-help@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.

Reply via email to