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Re: st: Poisson regression with score/scale as DV

From   Nick Cox <>
Subject   Re: st: Poisson regression with score/scale as DV
Date   Tue, 3 Apr 2012 09:40:49 +0100

That's Austin Nichols' presentation.

The folklore is that -poisson- works well even if the usual
assumptions are not well satisfied. Furthermore, as is customary, the
exact form of marginal distribution of the response is not part of the

So, I would try -poisson-. But since your response (you say DV)  is
also bounded, I would consider dividing by 27 and using -glm,
f(binomial)-. Why stick to one model when you can try two?


On Tue, Apr 3, 2012 at 8:58 AM, Clinton Thompson
<> wrote:

> Based on Austin Nichol's July 2010 presentation on use of Poisson for
> non-negative skewed variables
> ( as well
> as Bill Gould's Stata blog post about the same
> (,
> I'm considering Poisson for a problem I have, albeit the dependent
> variable is different enough from their examples that I'm unsure
> whether Poisson is entirely appropriate.  In my problem, the DV is a
> "score" assigned to each subject based on their responses to several
> component (ordinal scaled) questions.  This variable is bound between
> zero and 27 and the distribution of responses is decidedly non-normal
> (pile-up of responses at the zero value).  Any thoughts on whether
> Poisson is still a good candidate or should I be considering other
> approaches?  And if Poisson is not the right way to go, any advice on
> how to model this DV?
> I'm using Stata/SE 11.2 for Windows.

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