How to deal with overdispersion in Poisson regression: quasi-likelihood, negative binomial GLM, or subject-level random effect?
What better I use for Negative Binomial Regression with library(MASS) glm(family=negative.binomial) or glm.nb?
Why fitting a Poisson GLM in an over dispersed dataset underestimate the standard error of the regression parameter?
Can there be overdispersion in a logistic regression model where each observation represents a single Bernoulli trial?
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