I asked the following question on stack overflow yesterday: Negative binomial function in R
Reading comment 2, I understand that I cannot use a negative binomial modeling approach (a Poisson model works, but I suspect the assumption of equal mean and variance is invalid-though I'm uncertain as to how I can test this with an offset) and compare the betas to a reference category. I've googled and looked through my books but cannot find any other approach to compare multiple incidence rates.
b <- data.frame( s=c(1800,539,490,301), pop=c(2900000,1327000,880000,268000), reg=c("A","B","C","D") ) summary(pois.b<-glm(s~reg,offset=log(pop),data=b,family="poisson"))
So the question is : Is there any difference between the regions with regard to incidence?
Since the question yesterday was software related and today is more statistically flavored I figured it belonged here on cross-validated.
EDIT: Aug 11:
Since there are no other covariates here and the numbers are large I guess something as simple as
would get me a long way.