Generalized Linear Mixed Model

Generalized Linear Mixed Model. glmer() is a function to fit a generalized linear mixed-effects model from the lme4 library Thus generalized linear mixed models can easily accommodate the specific case of linear mixed models, but generalize further


from

The Generalized Linear Mixed Model (GLMM) is an extension of the Generalized Linear Model (GLM) that incorporates both fixed and random effects In statistics, a generalized linear mixed model (GLMM) is an extension to the generalized linear model (GLM) in which the linear predictor contains random effects in addition to the usual fixed effects

Such models are useful when the data are clustered in some way, a canonical example in education being students nested in schools Despite the availability of accurate techniques for estimating GLMM. Generalized linear mixed models (GLMMs) are a natural outgrowth of both linear mixed models and generalized linear models

. The interpretation of GLMMs is similar to GLMs; however, there is an added complexity because of the random effects Generalized linear mixed models extend linear mixed models, or hierarchical linear models, to accommodate noncontinuous responses, such as binary responses or counts

. It has arguments as follows: formula: A 2-sided linear formula object; Random-effects terms are distinguished by vertical bars (|) separating expressions for design matrices from grouping factors The Generalized Linear Mixed Model (GLMM) is an extension of the Generalized Linear Model (GLM) that incorporates both fixed and random effects