Hi All,
I am a beginner who is using Stata Version 11. Below is output for a
Random-Intercept Model: (1) the original data set, and (2) 5
imputations. What I would like to know is how to interpret output from
-mim: xtmixed- before I begin my analyses on the imputations. I found
a thread in the archives, but it did not address my question. I
understand what the output shows from -xtmixed- only. I do not
understand the random effects part of the -mim: xtmixed- output. I
would greatly appreciate any resources and/or suggestions. Thank you.
Best,
Frank
xtmixed pforce if _mj==0 || pd:, mle variance
Performing EM optimization:
Performing gradient-based optimization:
Iteration 0: log likelihood = -3790.7576
Iteration 1: log likelihood = -3790.7576
Computing standard errors:
Mixed-effects ML regression Number of obs
= 3300
Group variable: pd Number of groups
= 16
Obs per group: min
= 22
avg
= 206.2
max
= 696
Wald chi2(0)
= .
Log likelihood = -3790.7576 Prob > chi2
= .
------------------------------------------------------------------------------
pforce | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------
+----------------------------------------------------------------
_cons | 3.365989 .0380829 88.39 0.000
3.291348 3.44063
------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf.
Interval]
-----------------------------
+------------------------------------------------
pd: Identity |
var(_cons) | .0177083 .0073768 .
0078269 .040065
-----------------------------
+------------------------------------------------
var(Residual) | .5776353 .0142484 .
5503734 .6062477
------------------------------------------------------------------------------
LR test vs. linear regression: chibar2(01) = 102.86 Prob >= chibar2
= 0.0000
mim: xtmixed pforce || pd:, mle variance
Multiple-imputation estimates (xtmixed) Imputations
= 5
Mixed-effects ML regression Minimum obs
= 3300
Minimum dof
= 975.1
------------------------------------------------------------------------------
pforce | Coef. Std. Err. t P>|t| [95% Conf.
Int.] MI.df
-------------
+----------------------------------------------------------------
_cons | 3.36599 .038083 88.39 0.000 3.29126
3.44072 997.0
-------------
+----------------------------------------------------------------
/lns1_1_1 | -2.01686 .208286 -2.42559
-1.60813 998.0
/lnsig_e | -.274406 .012333 -.298609 -.
250203 975.1
------------------------------------------------------------------------------
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