I'm modelling overdispersed counts. I began using a GLM with Poisson error structure, then moved to quasi-Poisson, and then finally negative binomial. The residuals versus fitted values plot is still fan shaped and indicative of overdispersion. Is there a type of GLM that can handle this amount of overdispersion?
I've thought about using a hurdle-type approach, where smaller counts are modeled using Poisson or NB, and then the larger counts are modeled.
Any ideas for handling this amount of overdispersion?
Here is the code I've used:
glm.count.nb <- glm.nb(count ~ (year.range/year)*region*vegetation, data=data3) plot(glm.count.nb)
With these model diagnostic plots: