[email protected]
> I am trying to run a regression model having as depedent
> variable a count
> variable. The mean of this variable is 0.344 and the
> variance 0.745. I have
> tried to fit a negative binomial model to the data, but the
> alfa test is not
> significant, while the goodness of fit of the poisson model
> is much better.
> However, when I used the nbvargr command to obtain the
> parameter estimates and
> the relative graph the negative binomial distribution seems
> to fit better the
> data. Am I missing something?
I am not clear that you are comparing like with
like.
-nbvargr- does univariate fits without
covariates, whereas -nbreg- (is that what you are
using?) allows you to fit with or without covariates. Are you
fitting with covariates?
Setting that on one side, the tone of your report
does not seem that surprising, as the Poisson
is a limiting form of the negative binomial, and
-- for univariate fits, no covariates --
the comparison is thus between fitting the Poisson
with one parameter and fitting the negative binomial
with two. I can imagine cases in which the fit
of the more general distribution is better, but
various criteria of goodness of fit appear
to contradict that.
Nick
[email protected]
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