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Generalized Linear Mixed Models

Charles E. McCulloch

Abstract

Abstract Generalized linear mixed models (GLMMs) are a class of models that incorporates random effects into the linear predictor of a generalized linear model (GLM). This allows the modeling of correlated data within the context of GLMs and greatly extends their breadth of applicability. They thus include both linear mixed models (LMMs) and GLMs as special cases.

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Key concepts: Generalized linear mixed model, Generalized linear model, Hierarchical generalized linear model, Generalized linear array model, Applied mathematics, Linear model, Generalized additive model, Context (archaeology)