|
|  |
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]
Re: st: RE: RE: Count data regression
On Mar 23, 2006, at 12:00 PM, Rajesh Tharyan wrote:
Hi scott,
Re your reply to hugh..
2. For the Poisson MLE, valid inference requires equality of the
conditional
mean and variance (equidispersion) - it does not require that the
dependent
variable have a Poisson distribution.
I didn't get point two.. my impression was that it is the
distribution of
the underlying variable which sort of dictated whether you used a
poisson
regression or a nb regression..etc. but of course with a poission
distributed variable you always have mean=variance..
(Different Scott talking now).
When you don't have equidispersion, you lose precision in your
estimates, but you don't lose consistency. So the Poisson is still
consistent even if the conditional mean does not equal the
conditional variance. Thankfully, there are ways to correct the
standard errors for overdispersion. See the -poisson, robust- option
and the -xtpoisson, vce(boot)-. I don't have my Cameron and Trivedi
MICROECONOMETRICS handy, but if you look in there, they talk about
this correct procedure, and I think -poisson, robust- does this. -sc
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
