[R] subset selection for logistic regression

[Frank E Harrell Jr]

dr mike wrote:
>  
> 
> 
>>-----Original Message-----
>>From: r-help-bounces at stat.math.ethz.ch 
>>[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Wittner, Ben
>>Sent: 02 March 2005 11:33
>>To: r-help at lists.R-project.org
>>Subject: [R] subset selection for logistic regression
>>
>>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
>> 
>>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."
>>
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> 
> 
> The LASSO method and the Least Angle Regression method are two such that
> have both been implemented (efficiently IMHO - only one least squares for
> all levels of shrinkage IIRC) in the lars package for R of Hastie and Efron.
> There is a paper by Madigan and Ridgeway that discusses the use of the Least
> Angle Regresson approach in the context of logistic regression - available
> for download from Madigan's space at Ruttgers: 
> www.stat.rutgers.edu/~madigan/PAPERS/lars3.pdf 
> 
> HTH
> 
> Mike
Yes things like lasso can help a lot.
-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University