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st: Compute intraclass correlation coefficient after xtmelogit


From   Raquel Rangel de Meireles Guimarães <raquelrguimadem@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Compute intraclass correlation coefficient after xtmelogit
Date   Thu, 28 Jul 2011 23:54:24 -0300

Hi all,

Could you please give me and advice on how to compute the intraclass correlation coefficient after xtmelogit varying intercept model?

It seems that sd_resid is not reported...

Below you may find the output:

. xtmelogit excluido_leitura masculino branco pardo atrasado nse_transf c_nse_escola c_atraso_escola capitalcultural_
> transf ///
> envolvimento_transf motivacao_transf || escola: , or laplace

Refining starting values:

Iteration 0:   log likelihood = -1123816,5
Iteration 1:   log likelihood = -1119658,1
Iteration 2:   log likelihood = -1119658,1  (backed up)

Performing gradient-based optimization:

Iteration 0:   log likelihood = -1119658,1
Iteration 1:   log likelihood =   -1119378
Iteration 2:   log likelihood = -1119371,6
Iteration 3:   log likelihood = -1119371,6

Mixed-effects logistic regression Number of obs = 2102433 Group variable: escola Number of groups = 37300

Obs per group: min = 1 avg = 56,4 max = 518

Integration points = 1 Wald chi2(10) = 98039,45 Log likelihood = -1119371,6 Prob > chi2 = 0,0000

------------------------------------------------------------------------------
excluido_l~a | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
masculino | 1,486187 ,0050551 116,49 0,000 1,476312 1,496128 branco | ,7596705 ,0040705 -51,30 0,000 ,7517342 ,7676907 pardo | ,6731994 ,0034304 -77,66 0,000 ,6665094 ,6799565 atrasado | 2,03682 ,0077668 186,56 0,000 2,021654 2,0521 nse_transf | 1,053706 ,0015861 34,75 0,000 1,050602 1,05682 c_nse_esco~f | ,5189814 ,003619 -94,06 0,000 ,5119365 ,5261232 c_atraso_e~a | ,9864226 ,0229888 -0,59 0,557 ,9423789 1,032525 capitalcul~f | ,9296524 ,0014114 -48,05 0,000 ,9268902 ,9324228 envolvimen~f | ,8468481 ,0013563 -103,80 0,000 ,844194 ,8495105 motivacao_~f | 1,008081 ,0013549 5,99 0,000 1,005428 1,01074
------------------------------------------------------------------------------

------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
escola: Identity             |
sd(_cons) | ,6075827 ,0033232 ,6011041 ,6141311
------------------------------------------------------------------------------
LR test vs. logistic regression: chibar2(01) = 70351,01 Prob>=chibar2 = 0,0000

Note: log-likelihood calculations are based on the Laplacian approximation.

Thank you very much.

Best,

Raquel

--
Raquel Rangel de Meireles Guimarães
MA Student International&  Comparative Education
School of Education, Stanford University
http://stanford.academia.edu/RaquelGuimaraes

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