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Re: st: RE: comparing nested models after multiple imputation


From   Chelsea Garneau <chelsealynn.garneau@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: comparing nested models after multiple imputation
Date   Sun, 20 May 2012 21:09:53 -0400

Thank you, Kieran.  Would that be Wald tests using the F-statistic in
the output?  With df = 1?

On Sun, May 20, 2012 at 7:46 PM, Kieran McCaul <kieran.mccaul@uwa.edu.au> wrote:
> ...
>
> I think that this is currently a "work in progress" area and there is no method for performing LR tests with imputed data.
>
> The alternative is to use -mi test- and perform Wald tests.
>
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Chelsea Garneau
> Sent: Monday, 21 May 2012 3:08 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: comparing nested models after multiple imputation
>
> Hi Everyone,
>
> I'm trying to find a way to compare nested models using xtreg, xtlogit,
> xtmelogit, xtmixed after doing multiple imputation.  By "nested models" I
> mean subsequent models with additional predictors added, not multilevel -
> though my data are multilevel data as well. Because the LL's are not
> pooled, there is no e(ll) for the lrtest.  Rubin's rules combine parameter
> estimates and standard errors, not LL's, but what is the best way to test
> nested models using xt commands after mi?
>
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