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st: Compute intraclass correlation coefficient after xtmelogit
From
Raquel Rangel de Meireles Guimarães <[email protected]>
To
[email protected]
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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