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Re: st: NBREG for ordinal scales


From   Richard Williams <Richard.A.Williams.5@ND.Edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: NBREG for ordinal scales
Date   Tue, 10 Oct 2006 20:38:42 -0400

At 12:43 PM 10/10/2006, Timothy.Mak@iop.kcl.ac.uk wrote:
My feeling is: There's no particular reason we can only use Poisson or
NBin on count data. Surely the important thing is that the distribution
matches, right? In Poisson or NBin regression, we express results in terms
of Incidence Rate Ratio, which I guess only makes sense if you're thinking
of events happening. But what about calling it 'mean ratios', as
effectively they are just that?

I have no backing from any reference or anything, but just thinking
logically (I feel), that is what I would conclude. Richard, you don't
agree with using count-type regression techniques on non-count data. Why
is that?
For the ordinal variable in question, why would you expect the distribution to be right? 0 = never, 1 = 1 or 2, 2 = 3 or 4, 3 = 5 or more. In effect, the original count was collapsed, and in a somewhat arbitrary way; it could have just as easily been 1 = 1, or 1 = 1 or 2 or 3, or whatever. It may well be that the method doesn't work too badly (just like OLS regression may not give that horrible of results with a dichotomous outcome) but I'd be surprised if this was the optimal way to do things. Now, it may be that somebody somewhere spent a great deal of time validating this approach; but it may also be that somebody just did it, the reviewers didn't complain, and now it is semi-accepted practice.


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Richard Williams, Notre Dame Dept of Sociology
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