Re: [R] logistic regression model + Cross-Validation

From: Frank E Harrell Jr <f.harrell_at_vanderbilt.edu>
Date: Sun 21 Jan 2007 - 14:54:00 GMT

nitin jindal wrote:
> Hi,
>
> I am trying to cross-validate a logistic regression model.
> I am using logistic regression model (lrm) of package Design.
>
> f <- lrm( cy ~ x1 + x2, x=TRUE, y=TRUE)
> val <- validate.lrm(f, method="cross", B=5)

val <- validate(f, ...) # .lrm not needed

>
> My class cy has values 0 and 1.
>
> "val" variable will give me indicators like slope and AUC. But, I also need
> the vector of predicted values of class variable "cy" for each record while
> cross-validation, so that I can manually look at the results. So, is there
> any way to get those probabilities assigned to each class.
>
> regards,
> Nitin

No, validate.lrm does not have that option. Manually looking at the results will not be easy when you do enough cross-validations. A single 5-fold cross-validation does not provide accurate estimates. Either use the bootstrap or repeat k-fold cross-validation between 20 and 50 times.   k is often 10 but the optimum value may not be 10. Code for averaging repeated cross-validations is in
http://biostat.mc.vanderbilt.edu/twiki/pub/Main/RmS/logistic.val.pdf along with simulations of bootstrap vs. a few cross-validation methods for binary logistic models.

Frank

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

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Received on Mon Jan 22 01:59:29 2007

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