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st: ST: postestimation test


From   "Bontempo, Daniel E" <deb193@ku.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: ST: postestimation test
Date   Fri, 6 Aug 2010 09:38:40 -0500

I think I am not understanding something about the "test" command used
after xtmixed.

The model showed the interaction of two factors was significant, and I
thought I could use "test" to probe which pairs of means were actually
different. But some comparisons involving the reference condition do not
work, and I am not sure why the test is giving chisq. How can I do
pairwise comparisons here. For example below the means of 55 and 56.25
for levels of ageGroup within condition level 1 are unlikely to be
different. But I wanted to test if the means across ageGroup differed at
both condition level 0 and 2, or just one of these levels. But, I could
not test 29.375 vs 37.14286. I know it has to do with 0 being the
baseline condition, but I do not have full understanding.

Any insights appreciated.

-----

. margins condition#ageGrp

Adjusted predictions                              Number of obs   =
225

Expression   : Linear prediction, fixed portion, predict()

------------------------------------------------------------------------
------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
------
   condition#|
      ageGrp |
        0 0  |     29.375   3.797744     7.73   0.000     21.93156
36.81844
        0 1  |   37.14286   4.059959     9.15   0.000     29.18548
45.10023
        1 0  |      56.25   3.797744    14.81   0.000     48.80656
63.69344
        1 1  |         55   4.059959    13.55   0.000     47.04263
62.95737
        2 0  |      58.75   3.797744    15.47   0.000     51.30656
66.19344
        2 1  |   49.28571   4.059959    12.14   0.000     41.32834
57.24309
------------------------------------------------------------------------
------

. test 0.condition#1.ageGrp=1.condition#1.ageGrp

 ( 1)  [condCorr_pct]0b.condition#1o.ageGrp -
[condCorr_pct]1.condition#1.ageGrp = 0

           chi2(  1) =    1.38
         Prob > chi2 =    0.2402

. test 1.condition#1.ageGrp==2.condition#1.ageGrp

 ( 1)  [condCorr_pct]1.condition#1.ageGrp -
[condCorr_pct]2.condition#1.ageGrp = 0

           chi2(  1) =    1.14
         Prob > chi2 =    0.2847

. test 0.condition#0.ageGrp=0.condition#1.ageGrp

 ( 1)  [condCorr_pct]0b.condition#0b.ageGrp -
[condCorr_pct]0b.condition#1o.ageGrp = 0
       Constraint 1 dropped

           chi2(  0) =       .
         Prob > chi2 =         .

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