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Re: st: which -cmp- option to use for poisson model with count data?

From   Nick Cox <>
Subject   Re: st: which -cmp- option to use for poisson model with count data?
Date   Thu, 3 May 2012 09:23:26 +0100

I am not annoyed. I am concerned that time is being wasted because (a)
we don't have enough information to give you good replies and (b) you
don't seem to understand much of the advice being given you.

David said

"Unless the counts are high, count data can't be realistically modeled
as the outcome of a single underlying process consisting of a linear
functional plus a normally distributed error."

That was his advice about using -cmp-. He's the author and an expert.
If you want to go against his advice, that's your call, but in the
only example you have given, your counts have a maximum of 5.

Whether your count data can be treated as ordered probit is something
on which experts have different tastes and judgements. Counts that can
go 0,...,5 could be treated as graded variables 0 < 1 < 2 < 3 < 4 < 5.
I can't comment on the example you refer to, as I have not studied it.

On terminology: I wouldn't describe a counted variable as a
categorical variable, although counted variables do certainly appear
in categorical data analysis texts.


On Thu, May 3, 2012 at 8:51 AM, Laura R. <> wrote:
> Dear Nick,
> sorry, I didn't want to annoy you. I had understood that David Roodman
> said that -poisson- cannot be used with -cmp-.
> However, -poisson- does not seem the right method for my research anyways.
> So, I compared my dependent variable (number of experts) to the number
> of kids, which is treated as -oprobit- in the -cmp- example in
> Statalist. I don't really see a great difference between these
> variables.
> However, I will also try to find out about "binomial" models. Actually
> I don't know anything about these models, and how to estimate them in
> Stata. Neither have a seen a paper with a categorical variable like
> mine using this method.
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