From: Christian Hennig <fm3a004_at_math.uni-hamburg.de>

Date: Thu 03 Mar 2005 - 04:10:46 EST

Christian Hennig

Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg hennig_at_math.uni-hamburg.de, http://www.math.uni-hamburg.de/home/hennig/ >From 1 April 2005: Department of Statistical Science, UCL, London

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Mar 03 04:50:34 2005

Date: Thu 03 Mar 2005 - 04:10:46 EST

Perhaps I should not write it because I will discredit myself with this
but...

Is it really so wrong to use a stepwise method? Let's say I divide the sample into three parts and do variable selction on the first part, estimation on the second and test on the third part (this solves almost all problems Frank is talking about on p. 56/57 in his excellent book). Is there always a tractable alternative?

On Wed, 2 Mar 2005, Berton Gunter wrote:

> 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@stat.math.ethz.ch
**> > [mailto:r-help-bounces@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@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
**> >
**> > ______________________________________________
**> > R-help@stat.math.ethz.ch mailing list
**> > https://stat.ethz.ch/mailman/listinfo/r-help
**> > PLEASE do read the posting guide!
**> > http://www.R-project.org/posting-guide.html
**> >
**>
**> ______________________________________________
**> R-help@stat.math.ethz.ch mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
**>
*

Christian Hennig

Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg hennig_at_math.uni-hamburg.de, http://www.math.uni-hamburg.de/home/hennig/ >From 1 April 2005: Department of Statistical Science, UCL, London

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R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Mar 03 04:50:34 2005

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