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Home Blog week #9 – Overdispersion

week #9 – Overdispersion

In discrete response models, overdispersion occurs when there is more correlation in the data than is allowed by the assumptions that the model makes.

This excess correlation might manifest itself in clustering – groups of observations that are more similar to one another than to the remaining data.  This excessive correlation can indicate an incomplete model – predictors or interactions omitted, the need for transformations, or the presence of outliers.

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