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Re: st: double hurble


From   Tirthankar Chakravarty <[email protected]>
To   [email protected]
Subject   Re: st: double hurble
Date   Sat, 9 May 2009 20:16:51 +0100

http://www.stata.com/statalist/archive/2005-08/msg00745.html

1) Note however that these are not double hurdle models for _count_
data - where in my experience these are typically used (hurdle models
are mixed outcome models with a binary first outcome for participation
in an activity, and a truncated positive count outcome for amount of
participation; double hurdle models are non-negative counts in the
second outcome - entry with zero amount of participation is allowed):
http://epub.ub.uni-muenchen.de/1528/
Recommended paper if you are interested in double hurdles.

You can, very easily, fit independent double hurdle models in Stata:
http://www.stata-journal.com/article.html?article=st0040
Replace -ztnb- with -nbreg- or any other univariate count regression command.

2) Of course if you only want (independent) hurdle models - which is
typically the case - because it is count data, Joseph Hilbe has
numerous routines to do this:
ssc install hplogit
ssc install hnbreg
ssc install hgclg
ssc install hglogit
ssc install hnbclg

3) Dependent hurdle/double hurdle models are trickier; -gllamm-

ssc install gllamm, replace

 is one possible solution. Writing your own -ml- routine is another. I
don't think -cmp- (D. Roodman, SSC) supports count outcomes (?), else
that would be ideal.

4) The code provided is for continuous outcomes.
http://www.jstor.org/stable/2096488


T



On Sat, May 9, 2009 at 5:47 PM, CHE, Yi <[email protected]> wrote:
> Dear
> Is there any stata code for double hurble model now?
> Thank you very much!
>
>
>         Best Wishes
>
> Yours
> CHE, Yi
> Mphil year 2
> Division of Social Science
> Hong Kong University of Science and Technology
>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>



-- 
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recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
belongs to Flg(κ) (where v is the free variable of r).

*
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