"It is not inconceivable to me that a case could be made for a
count model, but it seems like you ought to be able (or forced) to
justify it rather than just do it!"
That is one of my primary problems. I see a number of articles using count
models for outcome variables such as those presented earlier, but no
justification was provided for doing so other than the fact that the DV
has a Poisson or negative binomial distribution. I assume that they should
provide justification for using these techniques, but does the
justification exist?
> At 03:59 PM 10/11/2006, Austin Nichols wrote:
>>Nick et al.--
>>The Poisson model really only needs E(y|x)=exp(xb) to get consistent
>>estimates of b, which is why it is the model of choice with a
>>nonnegative dependent variable (esp. one that is sometimes zero, and
>>is theoretically unbounded above). See Wooldridge
>>(http://www.stata.com/bookstore/cspd.html) p.651 and surrounding text:
>>"A nice property of the Poisson QMLE is that it retains some
>>efficiency for certain departures from the Poisson assumption," etc.
>>
>>This addresses why one would use a "count model" for non-count data,
>>but it does not address why one would use Poisson for an outcome
>>variable that is an ordinal scale, which I would think is crying out
>>for an ordered logit, or the like:
>>http://www.nd.edu/~rwilliam/gologit2
>
> Actually, there is an added wrinkle in the original problem: ordinal
> variables were summed to create composite scales. That summing and
> subsequent use of count models would still seem to be
> problematic. On the other hand, suppose the responses had been
> worded 0 = never, 1 = a few times, 2 = a moderate amount, and 3 = a
> lot. Would the summation seem more questionable then, or less
> so? And what method would be better - a count model or plain old
> OLS? It is not inconceivable to me that a case could be made for a
> count model, but it seems like you ought to be able (or forced) to
> justify it rather than just do it!
>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
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