I am looking for guidelines on how to interpret residual plots of glm models. Especially poisson, negative binomial, binomial models. What can we expect from these plots when the models are "correct"? (for example, we expect the variance to grow as the predicted value increases, for when dealing with a Poisson model)
I know the answers depend on the models. Any references (or general points to consider) will be helpful/appreciated.