--- "Lachenbruch, Peter" <[email protected]> wrote:
> The use of a continuous model for data in which there is a clump of
> zeros seems incorrect. There is no transformation that can remove
> this clump. The severity of the problem depends a bit on the size
> of the clump. In the hospital insurance data (wanting to estimate
> hospitalization costs in the policy holders) 95% of the population
> had no costs. Pretending that these were continuous would lead to
> some nonsense results. At the present time, I have a data set that
> has 32 out of 145 people with zeros. However, these are not
> necessarily identifiable since they could be slightly greater than
> zero. I'm gritting my teeth on this and pretending all is well.
> However, a histogram shows enormous skewness. I'll probably try a
> square root.
An alternative that might be useful would be to use
-zip varlist, inflate(_cons) vce(robust)- which is useful even you
don't have integer values on your dependend variable. Problem ofcourse
is that the reasoning behind these quasi maximum likelihood models is
asymptotic, and a samplesize of 145 with such a relatively complicated
model may not be large enough to reach the Wonderful Kingdom of
Asymptotia.
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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