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Re: st: comparing nested models after multiple imputation
From
Stas Kolenikov <[email protected]>
To
[email protected]
Subject
Re: st: comparing nested models after multiple imputation
Date
Sun, 20 May 2012 23:31:39 -0400
On Sun, May 20, 2012 at 3:08 PM, Chelsea Garneau
<[email protected]> wrote:
> 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?
Since MI and Rubin's rule only apply to point estimates and variances,
likelihood ratios are out of question, and you only have Wald tests to
use in this situation. To understand the relations between the
likelihood ratio, Wald, and score/Lagrange multiplier tests, read a
great exposition by Buse from ages ago in The American Statistician:
http://www.citeulike.org/user/ctacmo/article/890474.
--
---- Stas Kolenikov
-- http://stas.kolenikov.name
---- Senior Survey Statistician, Abt SRBI
-- Opinions stated in this email are mine only, and do not reflect the
position of my employer
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