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Re: st: weigths

From   Constantine Daskalakis <[email protected]>
To   [email protected]
Subject   Re: st: weigths
Date   Wed, 04 Aug 2004 10:56:03 -0400

At 05:20 AM 8/4/2004, Antonio Rodrigues Andres wrote:
The dependent variable is ln(d/p) where d=deaths and p is the
population. The log of the death rate ln(d/p) is normally distributed
with variance 1/E(d), where E(d) is the expected number of deaths. Since
E(d) is proportional to p, the variance of ln(d/p) is inversely
proportional to p, the population size which ranges in my application
from 100,000 to five million. This implies heteroskedasticity.
Observations should be weighted by the square root of the country
population. This is similar to covert OLS into GLS, weighting by the
variance inverse of the residuals.
My question is
regress ln(d/p) x1 x2 [w=pop] is that correct?
how about this alternative way to do it?

xi: regress ln(d/p) x1 x2 i.year di1-di15
predict e, residual
gen esq=e^2
xi: regress esq x1 x2 i.year di1-di15
predict v
xi: regress ln(d/p) x1 x2 i.year di1-di15 [w=1/v]

I would appreciate any suggestions or comments

Poisson regression?
Negative binomial regression?

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Constantine Daskalakis, ScD
Assistant Professor,
Biostatistics Section, Thomas Jefferson University,
211 S. 9th St. #602, Philadelphia, PA 19107
Tel: 215-955-5695
Fax: 215-503-3804
Email: [email protected]
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