over-estimation Negative Binomial models

Ben, 

this is a continuation of the query i posted on: 

http://r.789695.n4.nabble.com/GLM-and-Neg-Binomial-models-td3902173.html

I cannot give you a direct example (big dataset) of what i did aside from
what i have written:
fitpoisson <- glm((RESPONSE) ~ A  + B + 
offset(log(LENGTH)) + offset(log(LENGTH_OBSERVATION)),family="poisson",data=
dataset)  

fitneg <- glm.nb((RESPONSE) ~ A  + B + 
offset(log(LENGTH)) + offset(log(LENGTH_OBSERVATION)),data= dataset)

sum(fitted(fitpoisson))

[1] 373

sum(fitted(fitneg))

[1] 514

Observed data is 373....


Any thoughts?

tomas 

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