[R] subset selection for logistic regression

[Berton Gunter]

To clarify Frank's remark ...

A prominent theme in statistical research over at least the last 25 years
(with roots that go back 50 or more, probably) has been the superiority of
"shrinkage" methods over variable selection. I also find it distressing that
these ideas have apparently not penetrated much (at all?) into the wider
scientific community (but I suppose I shouldn't be surprised -- most
scientists still do one factor at a time experiments 80 years after Fisher).
Specific incarnations can be found in anything Bayesian, mixed effects
models for repeated measures, ridge regression, and the R packages lars and
lasso, among others.

I would speculate that aside from the usual statistics/science cultural
issues, part of the reason for this is that the estimators don't generally
come with neat, classical inference procedures: like it or not, many
scientists have been conditioned by their Stat 101 courses to expect P
values, so in some sense, we are hoisted by our own petard.

Just my $.02 -- contrary(and more knowledgeable) opinions welcome.

-- Bert Gunter
 

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Frank 
> E Harrell Jr
> Sent: Wednesday, March 02, 2005 5:13 AM
> To: Wittner, Ben
> Cc: r-help at lists.R-project.org
> Subject: Re: [R] subset selection for logistic regression
> 
> Wittner, Ben wrote:
> > R-packages leaps and subselect implement various methods of 
> selecting best or
> > good subsets of predictor variables for linear regression 
> models, but they do
> > not seem to be applicable to logistic regression models.
> >  
> > Does anyone know of software for finding good subsets of 
> predictor variables for
> > linear regression models?
> >  
> > Thanks.
> >  
> > -Ben
> 
> Why are these procedures still being used?  The performance 
> is known to 
> be bad in almost every sense (see r-help archives).
> 
> Frank Harrell
> 
> >  
> > p.s., The leaps package references "Subset Selection in 
> Regression" by Alan
> > Miller. On page 2 of the
> > 2nd edition of that text it states the following:
> >  
> >   "All of the models which will be considered in this 
> monograph will be linear;
> > that is they
> >    will be linear in the regression coefficients.Though 
> most of the ideas and
> > problems carry
> >    over to the fitting of nonlinear models and generalized 
> linear models
> > (particularly the fitting
> >    of logistic relationships), the complexity is greatly increased."
> 
> 
> -- 
> Frank E Harrell Jr   Professor and Chair           School of Medicine
>                       Department of Biostatistics   
> Vanderbilt University
> 
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