st: Hurdle model using Gamma distribution

[Leny Mathew <lenymathewc@gmail.com>]

Hello All,
             I'm trying to use a hurdle model to model continuous data
which has zeros due to the existence of a minimum detectable limit.
Instead of the Poisson or negative binomial distribution which seem to
be commonly used in hurdle models, I would like to to use the Gamma
distribution to model the continuous data. Since the Gamma
distribution is defined only for x >0, is it possible to develop this
by estimating the binomial model separately from the parameters of a
gamma regression model?
I wrote out the Log likelihood for this model in the same way as
described in http://www.stata-journal.com/sjpdf.html?articlenum=st0040
 and the equation can be written out as the sum of the log-likelihood
of the binary model and the log likelihood of the gamma model. However
I'm not sure if this is the right way to proceed.
On this data data set, I did run the Poisson hurdle model and the
negative Binomial hurdle model and compared it to the output of the
model I described above. The results of the three models are
remarkably similar.

Any comments would be greatly appreciated.

Thanks,

Leny

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