Modelling and analysing correlated non-normal data

We introduce a model class that includes many types of correlation structures for non-Gaussian models. We then show how to check the underlying model assumptions to discriminate between different correlation patterns and demonstrate how to select suitable models. Strawberry data are used to discuss the choice between fixed- and random-effect models for the fertility effect in agricultural experiments. Prostate-cancer data are used to demonstrate the method applied to the analysis of longitudinal studies and Scottish lip-cancer data to illustrate an application to spatial statistics.

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