Asumming the number of deaths follows a Poison distribution. Ln (d/p) is
approximately normally distributed with variance 1/E(d) where E(d) is
the number of expected deaths
>>> [email protected] 08/04/04 05:01PM >>>
no, i dont fit a poisson regression, i use as dep. variable the death
rate,
>>> [email protected] 08/04/04 04:56PM >>>
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.country i.year di1-di15
>predict e, residual
>gen esq=e^2
>xi: regress esq x1 x2 i.country i.year di1-di15
>predict v
>xi: regress ln(d/p) x1 x2 i.country i.year di1-di15 [w=1/v]
>
>I would appreciate any suggestions or comments
Poisson regression?
Negative binomial regression?
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________________________________________________________________
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