A generalized linear model is overdispersed when the conditional variance exceeds the variance prescribed by its response family and mean, for example for a unit-dispersion Poisson or binomial model. Unobserved heterogeneity or dependence among repeated observations can cause it. A generalized linear mixed model adds random effects for the corresponding clusters or subjects, thereby representing this heterogeneity and induced dependence.

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