Two ways of modelling overdispersion in non‐normal data

By Youngjo Lee, John A. Nelder. 2000

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Generalized additive models for location, scale and shape (2005, methodology): “Lee and Nelder (1996, 2000) suggested that the casewise overdispersion may depend on an indicator variable for the fourth visit, denoted here by V4.”
Modelling and analysing correlated non-normal data (2001, methodology): “This produces what is known as the intra-block analysis, and such an analysis is robust against assumptions about the random effects in HGLMs: see Lee and Nelder (2000b).”
Double hierarchical generalized linear models (2006, methodology): “Ma et al. (2003) and Ha and Lee (2005) showed that nonparametric base-line frailty models can be fitted by using Poisson HGLMs.”
Double hierarchical generalized linear models (with discussion) (2006, methodology): “Ma et al. (2003) and Ha and Lee (2005) showed that nonparametric base-line frailty models can be fitted by using Poisson HGLMs.”