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st: RE: xtmelogit post-estimation


From   "Verkuilen, Jay" <JVerkuilen@gc.cuny.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: xtmelogit post-estimation
Date   Tue, 24 Feb 2009 15:02:23 -0500

Vincenzio Carrieri wrote:

[big snip]

------------------------------------------------------------------------
------
  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf.
Interval]
-----------------------------+------------------------------------------
------
reg: Independent             |
                sd(quintp~1) |   .0797235   .0618246      .0174377
.3644875
                 sd(escluso) |   .0576097   .0192887      .0298881
.1110434
                   sd(_cons) |   .1716145   .0330082      .1177157
.250192
------------------------------------------------------------------------
------
LR test vs. logistic regression:     chi2(3) =    83.05   Prob > chi2 =
0.0000


This LR test is an omibus test of ALL random effects vs. none, i.e.,
ordinary logistic regression. Based on my cursory reading of what you
have here, you probably don't need quintp~1 and could probably do OK
without escluso but might want to keep it. This can be resolved with an
LR test between the random intercept model and the one with random
slopes, though because you are dealing with a parameter on the boundary
of the parameter space, you have to use the dreaded chibar distribution.


Also do you mean for these all to be independent? You may want to fit
several models and get AICs for each. 

I'd suggest holding the fixed effects constant and explicitly compare:

Fixed effects only
Random intercept
Random intercept + slopes (independent)
Random intercept + slopes (dependent)

JV



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