Congratulations to Stata Corp, the new Stata 8 looks great!
I'm curious about the capacity for hierarchical models in the new version;
xtreg for instance allows random intercepts, but not random slopes; when I
need mixed hierarchical models with both random intercepts and slopes I've
used and appreciate GLLAMM in Stata, but it runs quite slowly in Stata 7,
even under adaptive quadrature. I have had to turn to alternative programs
( S-Plus primarily) for running such models for primarily two reasons;
they run faster, enough faster that it makes a difference between working
with an extensive project feasible versus infeasible given the time
constraints imposed by trying to run them in Stata, and secondly I also
appreciate the ease of using predefined alternative variance and
correlation structures in S-Plus, as well as the graphical approach
facilitated by S-Plus. Stata 8's new graphics look really exciting, and
will undoubtedly give Stata an edge in graphical evaluation and application
to such models, but my other two concerns seem not to be addressed in the
new Stata.
I am a great fan of Dr. Rabe-Heskeths work ( the author of GLLAMM, who also
has a great book "A handbook of Statistical Analysis using Stata"), and was
hoping that perhaps GLLAMM would be hard wired in to the next Stata
upgrade, but I don't see it on the list of new statistical elements in
Stata 8. I seem to remember that her web site at one point suggested that
this would occur (hard wiring GLLAMM into Stata which would make it faster?)
I really like working in Stata, and will be very interested to see how much
faster GLLAMM runs in Stata 8. Are there plans to incorporate GLLAMM into
Stata rather than run it as an ado? Will this improve the speed? Or are
there other plans to enhance the capacity of Stata to run hierarchical
models? Requests for or inquiries about such capacities seem to come up
regularly on the list.
Thanks again for what looks like it is a great enhancement to Stata. I look
forward to test driving it as soon as it ships. i will be interested to
learn about the future prospects for increased capabilities for
hierarchical modeling in Stata.
