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st: local macro and xtmixed in stata 12 giving diff results


From   Clara Barata <maria.clara.barata@iscte.pt>
To   statalist@hsphsun2.harvard.edu
Subject   st: local macro and xtmixed in stata 12 giving diff results
Date   Fri, 17 Feb 2012 15:54:32 +0000

Hi!
Any idea why these two models below would give me slightly different results?
Thanks.
Clara

*Model1

xtmixed ptc_10_ interv ptc_09_ D2-D5 agrup saseAp09 saseBp09 saseCp09
compy_09 web_09 preesc secundario totalunos_09 ///
docenttot_09 docentPercfem_09 docidade_09 naodoctot_09  antigu_09
docdoutmest_09 ///
AMU10 APU10 || cescola:, cov(un) pweight(pscorewgt)  mle var

*Model2

local variables D2-D5 agrup saseAp09 saseBp09 saseCp09 compy_09 web_09
preesc secundario totalunos_09 ///
docenttot_09 docentPercfem_09 docidade_09 naodoctot_09  antigu_09
docdoutmest_09 ///
AMU10 APU10

xtmixed ptc_10_ interv ptc_09_ `variables' || cescola:, cov(un)
pweight(pscorewgt)  mle var

* Complete log

. local variables D2-D5 agrup saseAp09 saseBp09 saseCp09 compy_09
web_09 preesc secundario totalunos_09 ///
> docenttot_09 docentPercfem_09 docidade_09 naodoctot_09  antigu_09 docdoutmest_09 ///
> AMU10 APU10

. xtmixed ptc_10_ interv ptc_09_ `variables' || cescola:, cov(un)
pweight(pscorewgt)  mle var
Note: single-variable random-effects specification; covariance
structure set to identity
(1625 missing values generated)

Obtaining starting values by EM:

Performing gradient-based optimization:

Iteration 0:   log pseudolikelihood = -7629.1893
Iteration 1:   log pseudolikelihood = -7628.8716
Iteration 2:   log pseudolikelihood = -7628.8715

Computing standard errors:

Mixed-effects regression                        Number of obs      =      1359
Group variable: cescola                         Number of groups   =       361

                                                Obs per group: min =         1
                                                               avg =       3.8
                                                               max =         8


                                                Wald chi2(2)       =    329.84
Log pseudolikelihood = -7628.8715               Prob > chi2        =    0.0000

                              (Std. Err. adjusted for 361 clusters in cescola)
------------------------------------------------------------------------------
             |               Robust
     ptc_10_ |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      interv |   4.425498   .7011216     6.31   0.000     3.051325    5.799671
     ptc_09_ |   .4548144   .0289727    15.70   0.000      .398029    .5115999
       _cons |   47.83422   2.600319    18.40   0.000     42.73769    52.93075
------------------------------------------------------------------------------

------------------------------------------------------------------------------
                             |               Robust
  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
cescola: Identity            |
                  var(_cons) |   9.664571   2.245821      6.128909     15.2399
-----------------------------+------------------------------------------------
               var(Residual) |   42.38466   2.659331       37.4802    47.93088
------------------------------------------------------------------------------

.

. xtmixed ptc_10_ interv ptc_09_ D2-D5 agrup saseAp09 saseBp09
saseCp09 compy_09 web_09 preesc secundario totalunos_09 ///
> docenttot_09 docentPercfem_09 docidade_09 naodoctot_09  antigu_09 docdoutmest_09 ///
> AMU10 APU10 || cescola:, cov(un) pweight(pscorewgt)  mle var
Note: single-variable random-effects specification; covariance
structure set to identity
(1641 missing values generated)

Obtaining starting values by EM:

Performing gradient-based optimization:

Iteration 0:   log pseudolikelihood =  -7567.187
Iteration 1:   log pseudolikelihood = -7565.6155
Iteration 2:   log pseudolikelihood = -7565.6135
Iteration 3:   log pseudolikelihood = -7565.6135

Computing standard errors:

Mixed-effects regression                        Number of obs      =      1359
Group variable: cescola                         Number of groups   =       361

                                                Obs per group: min =         1
                                                               avg =       3.8
                                                               max =         8


                                                Wald chi2(23)      =    493.65
Log pseudolikelihood = -7565.6135               Prob > chi2        =    0.0000

                                  (Std. Err. adjusted for 361 clusters
in cescola)
----------------------------------------------------------------------------------
                 |               Robust
         ptc_10_ |      Coef.   Std. Err.      z    P>|z|     [95%
Conf. Interval]
-----------------+----------------------------------------------------------------
          interv |   4.098699   .5971533     6.86   0.000       2.9283
   5.269098
         ptc_09_ |   .4162623   .0267885    15.54   0.000     .3637578
   .4687669
              D2 |  -.5525483   .8820861    -0.63   0.531    -2.281405
   1.176309
              D3 |  -3.002324   .8082203    -3.71   0.000    -4.586407
  -1.418241
              D4 |  -3.811223    1.05004    -3.63   0.000    -5.869264
  -1.753181
              D5 |  -4.668435   1.141422    -4.09   0.000     -6.90558
  -2.431289
           agrup |   1.900642   .9238745     2.06   0.040     .0898816
   3.711403
        saseAp09 |  -5.459656   2.802486    -1.95   0.051    -10.95243
   .0331154
        saseBp09 |   5.247487   4.820744     1.09   0.276    -4.200997
   14.69597
        saseCp09 |  -5.374767   8.870566    -0.61   0.545    -22.76076
   12.01122
        compy_09 |  -.0563566   .0343605    -1.64   0.101     -.123702
   .0109889
          web_09 |   .0823975   .0430518     1.91   0.056    -.0019826
   .1667775
          preesc |   1.373344   1.237249     1.11   0.267    -1.051619
   3.798308
      secundario |   .3618894   .6426638     0.56   0.573    -.8977086
   1.621487
    totalunos_09 |   .0011173   .0018731     0.60   0.551    -.0025538
   .0047884
    docenttot_09 |  -.0349247    .023305    -1.50   0.134    -.0806017
   .0107524
docentPercfem_09 |  -.0630209   .0412631    -1.53   0.127    -.1438951
   .0178534
     docidade_09 |  -.3729159   .1935731    -1.93   0.054    -.7523122
   .0064805
    naodoctot_09 |  -.0240927   .0380972    -0.63   0.527    -.0987619
   .0505765
       antigu_09 |   .1846323   .1690689     1.09   0.275    -.1467367
   .5160014
  docdoutmest_09 |    .093919   .0949468     0.99   0.323    -.0921734
   .2800113
           AMU10 |  -1.187541   1.247426    -0.95   0.341    -3.632452
    1.25737
           APU10 |  -1.663058    1.27383    -1.31   0.192     -4.15972
    .833603
           _cons |   73.14461   8.145537     8.98   0.000     57.17965
   89.10957
----------------------------------------------------------------------------------

------------------------------------------------------------------------------
                             |               Robust
  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
cescola: Identity            |
                  var(_cons) |   7.148994   1.617105      4.588839    11.13748
-----------------------------+------------------------------------------------
               var(Residual) |   41.30718   2.560637      36.58133    46.64355
------------------------------------------------------------------------------

.
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