Code:
. xtmixed metabolism group##time || id:, var
Performing EM optimization:
Performing gradient-based optimization:
Iteration 0: log likelihood = 121.88734
Iteration 1: log likelihood = 122.32628
Iteration 2: log likelihood = 122.32652
Iteration 3: log likelihood = 122.32652
Computing standard errors:
Mixed-effects ML regression Number of obs = 67
Group variable: id Number of groups = 36
Obs per group:
min = 1
avg = 1.9
max = 2
Wald chi2(5) = 15.46
Log likelihood = 122.32652 Prob > chi2 = 0.0086
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metabolism | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
group |
2 | -.0126059 .0162712 -0.77 0.438 -.0444968 .0192849
3 | .0139877 .0177918 0.79 0.432 -.0208836 .0488591
|
2.time | .0323302 .0159135 2.03 0.042 .0011403 .0635201
|
group#time |
2 2 | -.0126164 .0223585 -0.56 0.573 -.0564382 .0312054
3 2 | -.0028619 .0243949 -0.12 0.907 -.0506751 .0449513
|
_cons | .1481151 .0112525 13.16 0.000 .1260605 .1701697
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Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
id: Identity |
var(_cons) | 3.38e-22 2.59e-21 1.02e-28 1.12e-15
-----------------------------+------------------------------------------------
var(Residual) | .0015194 .0002625 .001083 .0021318
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LR test vs. linear model: chibar2(01) = 0.00 Prob >= chibar2 = 1.0000
