Dear all
In the near future I will have to write my own estimation command for
the first time. It will be a mixed model, much like an ordered probit
where the cut-offs are known, with some extra parameters. I will need
the Huber-White-Sandwich variance estimator, and I want to estimate it
both with a two-step procedure and by maximum likelihood. I own a copy
of Stata 9 and have access to Stata 10 if necessary.
I'd be grateful for some guidance on where to start. Is -ml- the way
to go, or is it better to learn mata and use the optimization
functions that are listed on www.stata.com/capabilities/matrix.html
? Will the maximum likelihood estimation book by Gould, Pitblado, and
Sribney help in either case? Is there some other resource out there
that tells you how to do it in mata and -ml-, and what the differences
are? I should add that I have no previous experience of mata, but I
did both NC151 and NC152.
Thanks,
Eva
(Apologies if this appears twice; I posted it this morning but it did
not get through.)
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