[R] Bayesian regression stepwise function?

[Ravi Varadhan]

Frank,

I have heard this (i.e. only head-to-head comparisons are valid) and various
other folklores about AIC and BIC based model selection before, including
one that these information criteria are only applicable for comparing two
nested models.  

Where has it been demonstrated that AIC/BIC cannot be used to find the best
subset, i.e. the subset that is closest to the "true" model (assuming that
true model is contained in the set of models considered, and that maximum
likelihood estimation is used for estimating parameters in the models)?  

I would greatly appreciate any reference that shows this.

Best,
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_personal_pages/Varadhan.h
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-----Original Message-----
From: Frank E Harrell Jr [mailto:f.harrell at vanderbilt.edu] 
Sent: Friday, October 23, 2009 4:04 PM
To: Ravi Varadhan
Cc: JLucke at ria.buffalo.edu; 'Allan.Y'; r-help at r-project.org;
r-help-bounces at r-project.org
Subject: Re: [R] Bayesian regression stepwise function?

Ravi Varadhan wrote:
> The stepAIC() function in "MASS" can be used, with k = log(n), to
implement
> your suggestion of "quasi-Bayesian" stepwise selection using the BIC
> criterion.
> 
> Ravi.

Although many statisticians use BIC otherwise, it was only designed to 
compare two pre-specified models.

Frank

> 
>
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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_personal_pages/Varadhan.h
> tml
> 
>  
> 
>
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> 
> 
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
> Behalf Of JLucke at ria.buffalo.edu
> Sent: Friday, October 23, 2009 2:31 PM
> To: Allan.Y
> Cc: r-help at r-project.org; r-help-bounces at r-project.org
> Subject: Re: [R] Bayesian regression stepwise function?
> 
> The BIC (Raftery) can be used for quasi-Bayesian model selection, but it's

> not stepwise.   Ntzoufras shows how to use WinBUGS to conduct Bayesian 
> model selection, but again it's not stepwise
> 
> 
> Ntzoufras, I. (2002), 'Gibbs variable selection using BUGS', Journal of 
> Statistical Software 7(7), 1--19.
> Ntzoufras, I. (2009), Bayesian modeling using WinBUGS, Wiley, Hoboken, NJ.
> Raftery, A. E. (1995), 'Bayesian model selection in social research', 
> Sociological Methodology 25, 111-163.
> 
> 
> 
> 
> 
> 
> 
> "Allan.Y" <allany at cmu.edu> 
> Sent by: r-help-bounces at r-project.org
> 10/22/2009 01:09 PM
> 
> To
> r-help at r-project.org
> cc
> 
> Subject
> [R]  Bayesian regression stepwise function?
> 
> 
> 
> 
> 
> 
> 
> Hi everyone,
> 
> I am wondering if there exists a stepwise regression function for the
> Bayesian regression model.  I tried googling, but I couldn't find 
> anything. 
> I know "step" function exists for regular stepwise regression, but nothing
> for Bayes.
> 
> 
> Thanks


-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University