Hello
Using -gllamm-, I have fitted a model for censored outcomes with three
nested random effects (subjects are nested in group which are nested
in sessions). I only have random intercepts, not random slopes.
I followed the advice by Sophia Rabe-Hesketh in this post
http://www.stata.com/statalist/archive/2004-02/msg00789.html when
setting up my model. My -glamm- command reads
gllamm $yvar $xvars if Matching==1, offset(off) i(SubjectID GroupID
SID) fam(gauss binom) link(ident sprobit) /*
*/ lv(var) fv(var) from(c) copy adapt
Now I would like to obtain predictions like the ones we can compute
after -tobit- with the ystar(a,b) option, but taking into account the
random effects (BLUPs). My suspicion is that this is not very easy,
since Stata's official -xttobit- only offers ystar(a,b) predictions
where the random effect is assumed to be zero, and I have three random
effects, not one.
I can get the linear prediction, including random effects, via
-gllapred- with the linpred option. Using this, I could obviously
apply the standard formula for the expectation of a truncated normal
distribution, but this sounds a bit too simple in such a complicated
model.
I'd be glad to hear comments about this procedure.
Many thanks,
Eva
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