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st: RE: comparing nested models after multiple imputation


From   Kieran McCaul <kieran.mccaul@uwa.edu.au>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: comparing nested models after multiple imputation
Date   Mon, 21 May 2012 07:46:05 +0800

...

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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