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st: xtmixed


From   Schöler, Lisa <lschoeler@wiwi.uni-frankfurt.de>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: xtmixed
Date   Thu, 7 Oct 2010 12:23:25 +0000

Dear Statalist,

I am having trouble with the command .xtmixed. After using the command below I get this output.
Now I want to get an output with the individual betas for the independent variables for every SIC code. Can anybody help me with that?
I also know that I have serial correlation problems in my data set, can anyone tell me how I can control for that within the xtmixed command?

Thank you very much
Lisa

.xtmixed q0 number_brands market_share intensity satisfaction channels margin sga0 rd0 cogs0 lppe0 income0 lassets0 leverage0 ||  SIC_twodigits: _brands market_share intensity satisfaction channels margin


Performing EM optimization: 

Performing gradient-based optimization: 

Iteration 0:   log restricted-likelihood = -403.08991  
Iteration 1:   log restricted-likelihood = -402.91597  
Iteration 2:   log restricted-likelihood = -402.73407  
Iteration 3:   log restricted-likelihood =  -402.6765  
Iteration 4:   log restricted-likelihood = -402.67649  

Computing standard errors:

Mixed-effects REML regression                   Number of obs      =      1584
Group variable: SIC_twodigits                   Number of groups   =        41

                                                Obs per group: min =         1
                                                               avg =      38.6
                                                               max =       223


                                                Wald chi2(13)      =    191.59
Log restricted-likelihood = -402.67649          Prob > chi2        =    0.0000

------------------------------------------------------------------------------
          q0 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
number_brands|   6.07e-07   3.26e-07     1.86   0.063    -3.17e-08    1.25e-06
market_share |   4.82e-07   5.35e-07     0.90   0.368    -5.67e-07    1.53e-06
   intensity |  -2.89e-07   1.89e-07    -1.53   0.127    -6.61e-07    8.19e-08
satisfaction |   1.13e-06   1.23e-06     0.91   0.362    -1.29e-06    3.55e-06
    channels |   8.73e-07   6.75e-07     1.29   0.196    -4.51e-07    2.20e-06
      margin |  -1.01e-07   1.81e-06    -0.06   0.956    -3.65e-06    3.45e-06
        sga0 |  -.2298161   .0529948    -4.34   0.000    -.3336839   -.1259482
         rd0 |   .4689618   .2057867     2.28   0.023     .0656273    .8722963
       cogs0 |  -.0318355   .0196152    -1.62   0.105    -.0702805    .0066095
       lppe0 |   .0773692   .0123622     6.26   0.000     .0531397    .1015986
     income0 |   2.25e-06   1.05e-06     2.13   0.033     1.80e-07    4.31e-06
    lassets0 |  -.1549344   .0140697   -11.01   0.000    -.1825104   -.1273583
   leverage0 |   .0466289   .0314185     1.48   0.138    -.0149503    .1082081
       _cons |   1.733769   .0847409    20.46   0.000     1.567679    1.899858
------------------------------------------------------------------------------

------------------------------------------------------------------------------
  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
SIC_twodig~s: Independent    |
           sd(number_brands) |   1.41e-06   3.05e-07      9.24e-07    2.16e-06
            sd(market_share) |   1.90e-06   5.43e-07      1.09e-06    3.33e-06
               sd(intensity) |   3.25e-07   4.29e-07      2.46e-08    4.30e-06
             d(satisfaction) |   4.52e-06   1.41e-06      2.46e-06    8.33e-06
                sd(channels) |   2.35e-06   7.48e-07      1.26e-06    4.39e-06
                  sd(margin) |   3.19e-06   2.16e-06      8.44e-07     .000012
                   sd(_cons) |    .213759   .0411126      .1466262    .3116286
-----------------------------+------------------------------------------------
                sd(Residual) |   .2680915   .0051176      .2582465    .2783118
------------------------------------------------------------------------------
LR test vs. linear regression:       chi2(7) =   486.25   Prob > chi2 = 0.0000

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


Lisa Schöler
Professur für BWL, insb. Electronic Commerce
Goethe-Universität Frankfurt
Grüneburgplatz 1 
60629 Frankfurt a.M.
 
Phone: ++49 69 798 34632
Fax:   ++49 69 798 35001
Email: lschoeler@wiwi.uni-frankfurt.de
URL:   www.ecommerce.wiwi.uni-frankfurt.de

_________________________________
Get serious about better marketing decisions - apply now!
http://www.goethe-master.de



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