I am trying to fit a linear mixed model using xtmixed with two random
coefficients and a random intercept, using the following syntax:
xtmixed depvar xvar1 xvar2 [otherxvars] if touse || groupid : xvar1 xvar2,
covariance(unstruct)
The model appears to converge, but two of the standard errors are missing,
as shown below (all other standard errors are present):
----------------------------------------------------------------------------
--
Random-effects Parameters | Estimate Std. Err. [95% Conf.
Interval]
-----------------------------+----------------------------------------------
--
groupid: Unstructured |
sd(xvar1) | .5210501 .0146728 .4930711
.5506168
sd(xvar2) | .7152157 .0202753 .6765606
.7560793
sd(_cons) | 3.777054 .1089148 3.569505
3.996671
corr(xvar1,xvar2) | -.8403815 . .
.
corr(xvar1,_cons) | .2627643 .0004142 .2619524
.2635758
corr(xvar2,_cons) | -.739374 . .
.
-----------------------------+----------------------------------------------
--
sd(Residual) | .8609064 .0026954 .8556397
.8662056
----------------------------------------------------------------------------
--
LR test vs. linear regression: chi2(6) = 6855.91 Prob > chi2 =
0.0000
I'm not sure how to interpret this. Does it mean that the model has not
actually converged? There are a number of "(not concave)" error messages in
the iteration log, but no problems are reported in the final 5 iterations.
Any suggestions for fixing the problem would be very gratefully received.
I'm reluctant to impose a covariance structure, as there's little reason to
think this is theoretically justified (indeed, part of my substantive
interest is in the unstructured covariance estimates).
Thanks in advance,
Glenn.
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