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Re: st: RE: RE: Hurdle model using Gamma distribution


From   Leny Mathew <lenymathewc@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: RE: Hurdle model using Gamma distribution
Date   Thu, 29 Jul 2010 08:38:35 -0400

Thank You, Tony for the suggestion, and Nick for the reference.

On Mon, Jul 26, 2010 at 6:06 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
> Full references please!
>
> Peter A Lachenbruch
> Analysis of data with excess zeros
> Stat Methods Med Res August 2002 11: 297-302,
> doi:10.1191/0962280202sm289ra
>
> Nick
> n.j.cox@durham.ac.uk
>
> Lachenbruch, Peter [Tony]
>
> See Lachenbruch, SMMR 2002 for a special issue on this.  I did some work using a log-normal plus excess zeros.
>
> Leny Mathew
>              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.
>
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