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Re: st: Backward Selection (AIC) with xtmixed


From   SR Millis <[email protected]>
To   [email protected]
Subject   Re: st: Backward Selection (AIC) with xtmixed
Date   Sat, 16 Jul 2011 12:08:51 -0700 (PDT)

The problems with the various flavors of stepwise variable selection (including forward and backward selection) have been discussed quite exhaustively on Statalist (search the archives).  In short, the models/variables selected by stepwise methods tend to be unstable and often do not replicate well.  

Scott Millis



--- On Fri, 7/15/11, Allan Kennedy <[email protected]> wrote:

> From: Allan Kennedy <[email protected]>
> Subject: Re: st: Backward Selection (AIC) with xtmixed
> To: [email protected]
> Date: Friday, July 15, 2011, 10:53 PM
> Could you provide a deeper rationale
> as to why this approach is not
> recommended?/
> 
> On Fri, Jul 15, 2011 at 10:44 PM, SR Millis <[email protected]>
> wrote:
> > This procedure is not recommended.
> >
> >
> > ~~~~~~~~~~~
> > Scott R Millis, PhD, ABPP, CStat, PStat®
> > Professor
> > Wayne State University School of Medicine
> > Email:  [email protected]
> > Email:  [email protected]
> > Tel: 313-993-8085
> >
> >
> > --- On Fri, 7/15/11, Allan Kennedy <[email protected]>
> wrote:
> >
> >> From: Allan Kennedy <[email protected]>
> >> Subject: st: Backward Selection (AIC) with
> xtmixed
> >> To: [email protected]
> >> Date: Friday, July 15, 2011, 10:36 PM
> >> Greetings,
> >>
> >> I am interesting is using an automated command
> that will
> >> estimate
> >> model fit with a backward selection model with AIC
> of an
> >> --xtmixed--
> >> approach. I know that both --stepwise-- and
> --swaic-- both
> >> do not
> >> support xtmixed but I wanted to see if there were
> any other
> >> user
> >> written programs that support --xtmixed--. An
> example of my
> >> code is as
> >> follows:
> >>
> >> xtmixed OUTCOME  10PREDICTORS  CONTROL
> VARIABLES
> >> ||RANDOM_1:
> >> ||RANDOM_2: ||RANDOM_3: , covariance(unstructured)
> var mle
> >>
> >> I would like to estimate the lowest AIC model of
> any
> >> combination of
> >> the 10 predictors.
> >>
> >> Your assistance would be greatly appreciated.
> >>
> >>
> >> --AK
> >> *
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> >>
> >
> > *
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> >
> 
> *
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