[R] Stepwise GLM selection by LRT?

[Ravi Varadhan]

Check out the stepAIC function in MASS package.  This is a nice tool, where
you can actually implement any penalty even though the function's name has
"AIC" in it because it is the default.  Although this doesn't do an LRT test
based variable selection, you can sort of approximate it by using a penalty
of k = qchisq(1-p, df=1), where p is the p-value for variable selection.
This penalty means that a variable enters/exits an existing model, when the
absolute value of change in log-likelihood is greater than qchisq(1-p,
df=1). For p = 0.1, k = 2.71, and for p=0.05, k = 3.84.  Is this whhant
you'd like to do?
 
Ravi.

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Ravi Varadhan, Ph.D.

Assistant Professor, The Center on Aging and Health

Division of Geriatric Medicine and Gerontology 

Johns Hopkins University

Ph: (410) 502-2619

Fax: (410) 614-9625

Email: rvaradhan at jhmi.edu

Webpage:  http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html

 

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-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Lutz Ph. Breitling
Sent: Wednesday, July 11, 2007 3:06 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Stepwise GLM selection by LRT?

Dear List,

having searched the help and archives, I have the impression that
there is no automatic model selection procedure implemented in R that
includes/excludes predictors in logistic regression models based on
LRT P-values. Is that true, or is someone aware of an appropriate
function somewhere in a custom package?

Even if automatic model selection and LRT might not be the most
appropriate methods, I actually would like to use these in order to
simulate someone else's modeling approach...

Many thanks for all comments-
Lutz
-----
Lutz Ph. Breitling
German Cancer Research Center
Heidelberg/Germany

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