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st: meglm
From
Alfonso S <[email protected]>
To
Stata List <[email protected]>
Subject
st: meglm
Date
Wed, 16 Oct 2013 05:00:46 -0700 (PDT)
Hi,
I am trying to get my head around using the -meglm- command in Stata 13 for the mac, and I must be doing something wrong. The following are the results I get when running it:
----------------------------------------------
. meglm ysm ldis_totcurexpppa sch_enrlunsh lsch_enrtotal y_dum2 y_dum3 y_dum4 y_dum5 y_dum6 y_dum7 y_dum8 mldis_totcurexppp mlunch mlenrol || sprp_sch:, covariance(exchangeable) family(binomial) link(probit)
Fitting fixed-effects model:
Iteration 0: log likelihood = -2347.0075
Iteration 1: log likelihood = 0
Iteration 2: log likelihood = 0
Refining starting values:
Grid node 0: log likelihood = -8.835e-06
Fitting full model:
Iteration 0: log likelihood = -8.835e-06 (not concave)
Iteration 1: log likelihood = -1.147e-12
Iteration 2: log likelihood = -1.142e-12
Mixed-effects GLM Number of obs = 6856
Family: binomial
Link: probit
Group variable: sprp_sch Number of groups = 857
Obs per group: min = 8
avg = 8.0
max = 8
Integration method: mvaghermite Integration points = 7
Wald chi2(0) = .
Log likelihood = -1.142e-12 Prob > chi2 = .
-----------------------------------------------------------------------------------
ysm | Coef. Std. Err. z P>|z| [95% Conf. Interval]
------------------+----------------------------------------------------------------
ldis_totcurexpppa | -.6370373 . . . . .
sch_enrlunsh | 3.177517 . . . . .
lsch_enrtotal | .0229953 . . . . .
y_dum2 | .699251 . . . . .
y_dum3 | .8369304 . . . . .
y_dum4 | .7515347 . . . . .
y_dum5 | .6936224 . . . . .
y_dum6 | .6023263 . . . . .
y_dum7 | .6499135 . . . . .
y_dum8 | .6696426 . . . . .
mldis_totcurexppp | .3410811 . . . . .
mlunch | 6.249509 . . . . .
mlenrol | .0017366 . . . . .
_cons | 12.76935 . . . . .
------------------+----------------------------------------------------------------
sprp_sch |
var(_cons)| .5950633 . . .
-----------------------------------------------------------------------------------
LR test vs. probit regression: chi2(0) = 0.00 Prob > chi2 = .
Note: LR test is conservative and provided only for reference.
-----------------------------------------------
To see that the variables were doing fine I ran the -xtgee- estimation and got normal results
-----------------------------------------------
. xtgee ysm ldis_totcurexpppa sch_enrlunsh lsch_enrtotal y_dum2 y_dum3 y_dum4 y_dum5 y_dum6 y_dum7 y_dum8 mldis_totcurexppp mlunch mlenrol, family(binomial) link(probit) corr(exch)
Iteration 1: tolerance = .21314375
Iteration 2: tolerance = .00124994
Iteration 3: tolerance = .00001481
Iteration 4: tolerance = 3.957e-07
GEE population-averaged model Number of obs = 6856
Group variable: sprp_sch Number of groups = 857
Link: probit Obs per group: min = 8
Family: binomial avg = 8.0
Correlation: exchangeable max = 8
Wald chi2(13) = 113.63
Scale parameter: 1 Prob > chi2 = 0.0000
-----------------------------------------------------------------------------------
ysm | Coef. Std. Err. z P>|z| [95% Conf. Interval]
------------------+----------------------------------------------------------------
ldis_totcurexpppa | .2161359 .3463714 0.62 0.533 -.4627396 .8950114
sch_enrlunsh | -.0725626 .2464216 -0.29 0.768 -.5555401 .4104148
lsch_enrtotal | -.0349141 .1043114 -0.33 0.738 -.2393606 .1695323
y_dum2 | -.1418307 .0822838 -1.72 0.085 -.3031039 .0194425
y_dum3 | -.2154219 .0750023 -2.87 0.004 -.3624236 -.0684201
y_dum4 | -.1581733 .0651644 -2.43 0.015 -.2858932 -.0304533
y_dum5 | -.1202846 .0596719 -2.02 0.044 -.2372394 -.0033298
y_dum6 | -.0590736 .0576424 -1.02 0.305 -.1720506 .0539034
y_dum7 | -.0919327 .0537733 -1.71 0.087 -.1973266 .0134611
y_dum8 | -.1063621 .0504099 -2.11 0.035 -.2051636 -.0075606
mldis_totcurexppp | -.0413327 .4116867 -0.10 0.920 -.8482237 .7655583
mlunch | -1.001581 .2810579 -3.56 0.000 -1.552444 -.4507177
mlenrol | .0000284 .0003227 0.09 0.930 -.0006039 .0006608
_cons | -.3508665 2.187324 -0.16 0.873 -4.637943 3.93621
-----------------------------------------------------------------------------------
---------------------------------------------------------------------------------------
Can someone tell me if I am specifying the meglm command wrong? If not, why does it not reproduce the results from xtgee?
Thanks,
Alfonso.
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