annie Zhang wrote:
Hi, Frank,
You mean the backward and forward stepwise selection is bad? You also
suggest the penalized logistic regression is the best choice? Is there
any function to do it as well as selecting the best penalty?
Annie
All variable selection is bad unless its in the context of penalization.
You'll need penalized logistic regression not necessarily with
variable selection, for example a quadratic penalty as in a case study
in my book, or an L1 penalty (lasso) using other packages.
Frank
On Wed, Sep 2, 2009 at 7:41 PM, Frank E Harrell Jr
<f.harr...@vanderbilt.edu <mailto:f.harr...@vanderbilt.edu>> wrote:
David Winsemius wrote:
On Sep 2, 2009, at 9:36 PM, annie Zhang wrote:
Hi, R users,
What may be the best function in R to do variable selection
in logistic
regression?
PhD theses, and books by famous statisticians have been pursuing
the answer to that question for decades.
I have the same number of variables as the number of samples,
and I want to select the best variablesfor prediction. Is
there any function
doing forward selection followed by backward elimination in
stepwise
logistic regression?
You should probably be reading up on penalized regression
methods. The stepwise procedures reporting unadjusted
"significance" made available by SAS and SPSS to the unwary
neophyte user have very poor statistical properties.
--
David Winsemius, MD
Amen to that.
Annie, resist the temptation. These methods bite.
Frank
Heritage Laboratories
West Hartford, CT
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--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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