Hi Derek Darves,
the level 1 variance should be given immediately
under the table for the regression coefficients under
the heading
Variance at level 1
---------------------
before the variances of the random effects.
If you want a random intercept and a random slope for a
covariate x, you can use the commands
gen cons=1
eq inter: cons
eq slope: x
gllamm y x, i(id) eqs(inter slope) ...
You may find the Stata textbook examples at the UCLA Academic
Technology Services webpage useful:
e.g.
http://www.ats.ucla.edu/stat/stata/examples/mlm_imm/immch3.htm
These can also be accessed via the gllamm webpage -
see 'worked examples':
http://www.iop.kcl.ac.uk/IoP/Departments/BioComp/programs/gllamm.html
Best wishes,
Sophia
I am trying to replicate some models in run SAS with proc mixed using
the gllamm command in Stata. At the moment, I cannot get gllamm to
print the level 1 and level 2 random effects estimates, i.e. what SAS
refers to as the "Covariance Parameter Estimates" in its output. Thus
far, gllamm reports the following output for the random effects:
***level 2 (site9)
var(1): .598095 (.06353876)
, which I presume is for the level 2, intercept variance. How can I
also get an estimate for the level 1 residual variance, which I would
like in order to compare the amount of variance to be explained at each
level (in the intercept-only model).
Also, can someone please explain how the eq command operates in gllamm?
In corresponding with the author of gllamm, I have learned that in
order to allow the intercept to vary I must first create a constant and
link it using the eq function. How do you accomplish the same when, for
example, you'd like one of the slopes to vary randomly?
Thanks,
Derek Darves
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