-------------------------------------------------------------------------------
      name:  <unnamed>
       log:  Q:\C-modelling\runmlwin\website\logfiles\2020-03-27\16\12.4.smcl
  log type:  smcl
 opened on:  27 Mar 2020, 18:23:58

. ****************************************************************************
. * Module 12: Cross-Classified Models - Stata Practical
. *
. *     P12.4: Adding a Random School-by-Neighbourhood Interaction Classificati
> on
. *
. *            George Leckie
. *            Centre for Multilevel Modelling, 2011
. ****************************************************************************
. *     Stata do-file to replicate all analyses using runmlwin
. *
. *     George Leckie
. *     Centre for Multilevel Modelling, 2013
. *     http://www.bristol.ac.uk/cmm/software/runmlwin/
. ****************************************************************************
. 
. use "http://www.bristol.ac.uk/cmm/media/runmlwin/12.4.dta", clear

. 
. egen schidXneighid = group(schid neighid)

. 
. xtmixed attain || _all: R.schid || neighid: || schidXneighid:, mle variance

Performing EM optimization: 

Performing gradient-based optimization: 

Iteration 0:   log likelihood = -3179.4012  
Iteration 1:   log likelihood = -3176.3704  
Iteration 2:   log likelihood = -3176.2883  
Iteration 3:   log likelihood = -3176.2863  
Iteration 4:   log likelihood = -3176.2863  

Computing standard errors:

Mixed-effects ML regression                     Number of obs     =      2,310

-------------------------------------------------------------
                |     No. of       Observations per Group
 Group Variable |     Groups    Minimum    Average    Maximum
----------------+--------------------------------------------
           _all |          1      2,310    2,310.0      2,310
        neighid |        524          1        4.4         16
   schidXneig~d |        784          1        2.9         14
-------------------------------------------------------------

                                                Wald chi2(0)      =          .
Log likelihood = -3176.2863                     Prob > chi2       =          .

------------------------------------------------------------------------------
      attain |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |    .074952   .0723328     1.04   0.300    -.0668176    .2167216
------------------------------------------------------------------------------

------------------------------------------------------------------------------
  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
_all: Identity               |
                var(R.schid) |   .0757556   .0320221      .0330833    .1734684
-----------------------------+------------------------------------------------
neighid: Identity            |
                  var(_cons) |   .0907447   .0335894      .0439285    .1874546
-----------------------------+------------------------------------------------
schidXneig~d: Identity       |
                  var(_cons) |   .0683918   .0365682      .0239816    .1950428
-----------------------------+------------------------------------------------
               var(Residual) |    .781917   .0271383      .7304957     .836958
------------------------------------------------------------------------------
LR test vs. linear model: chi2(3) = 211.57                Prob > chi2 = 0.0000

Note: LR test is conservative and provided only for reference.

. 
. estimates store model3

. 
. lrtest model1 model3

Likelihood-ratio test                                 LR chi2(1)  =      4.14
(Assumption: model1 nested in model3)                 Prob > chi2 =    0.0419

Note: The reported degrees of freedom assumes the null hypothesis is not on
      the boundary of the parameter space.  If this is not true, then the
      reported test is conservative.

. 
end of do-file