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# Re: st: Regression Equation for Zero inflated negative binomial

 From rachel grant To statalist@hsphsun2.harvard.edu Subject Re: st: Regression Equation for Zero inflated negative binomial Date Tue, 20 Sep 2011 10:10:23 +0100

```Thanks to everyone but I am still very confused. I should explain, I
am not a mathematician, I dont understand mathmatical formulae, I am a
biologist. I am looking for a regression formula for ZINB but I cannot
find anything that resembles:  ln (Y) + B0+B1X1 + B2X2.
Yes there are formulae in the resources you are all pointing me to but
none of them look like a regression equation, and they dont have X on
the right hand side. I can't buy expensive books... I have been
searching help file and internet resources for several months.

thanks
Rachel Grant

2011/9/19 rachel grant <rachelannegrant@gmail.com>:
> Thank you for your help. Maybe I need to explain the problem more clearly
> I have used Zero Inflated negative binomial regression in Stata to
> model some overdispersed, zero inflated count data. I got very nice
> results and also used the postestimation tools to predict Y values.
> This is included in my PhD thesis which I am about to submit. My PhD
> supervisor said as well as presenting the results (i.e cofficients, p
> values etc.) I also have to show "the model". I think by this he means
> the regression equation in the form:
>
> natural log (Y) = B0+B1X1 + B2X2..............
>
> I cannot find out what the equation is for ZINB models and also I
> cannot find out how to make Stata display this model.
> I could just add in the coefficients myself BUT I am not sure of the
> exact formula of the model for ZINB (especially the ZI part) as I
> think it may be more complicated than the simple Poisson
>
> log e  (Y) = β0 + β1Χ1 + β2Χ2 ...
>
> I have searched everywhere to find a general equation for ZINB with no
> luck and also read all the Stata help files.
> I am very confused about why this seemingly simple thing should prove
> so impossible! I am a beginner with stata, and previously only used
> simple linear regression so thank you for your patience.
>
> --
> regards, Rachel Grant
>
> *
> *   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/
>

--
regards, Rachel

*
*   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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