use http://www.ats.ucla.edu/stat/stata/examples/kirk/rb4, clear
anova y a s, repeated(a)
test _coef[a[3]] = _coef[a[4]]
anova, regress // note a[4] was dropped
xi: xtmixed y i.a || s: // note a[1] was dropped
test _Ia_3 = _Ia_4
display r(chi2)/r(df) // scale to show F the same, but here df 1
...shows the same results, yes, and wrt your question, the
coefficients shown are relative to the dropped group, in this model.
You can also change which group gets dropped.
On Dec 31, 2008, at 8:37 AM, Paul Bransom wrote:
Sorry - forgot the subject on my earlier posting
Hello,
I am trying to teach myself how to use xtmixed for repeated measures
anova. Using anova:
anova m method id,repeated(method)
I have a significant effect of method and I can compare the methods:
test _coef[method[1]] = _coef[method[2]] ( 1) method[1] -
method[2] = 0
F( 1, 27) = 58.27
Prob > F = 0.0000
However when I use xtmixed
xi:xtmixed m i.method || id:
-----
------------------------------------------------------------------------------
m | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------
+----------------------------------------------------------
-------------+------
_Imethod_2 | -12.6 1.650589 -7.63 0.000 -15.8351
-9.364905
_Imethod_3 | -15.1 1.650589 -9.15 0.000 -18.3351
-11.8649
_Imethod_4 | -11.1 1.650589 -6.72 0.000 -14.3351
-7.864905
_cons | 38.6 2.253023 17.13 0.000 34.18416
43.01584
I can again compare all the methods:
. test _Imethod_2 = _Imethod_3
with the exception of method 1 as _Imethod_ is the "reference" in
the equation.
My question is - how can I compare the effect of method 1 to the
other methods or is the fact that these coefficients have a
significant p value sufficient (or am I missing something that is so
obvious)?
I am using Stata 10.
Thanks,
Paul
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