This chapter introduces mixed-effects models that combine fixed and random effects. Fixed and random effects are compared and contrasted and the differences in the R output compared with linear models and GLMs are explained. The relationship between variances and variance components is demonstrated. The R code necessary to perform the analysis is demonstrated and explained in terms of the underlying statistical concepts and the interpretation of the R output demonstrated. The results are presented using R graphics and text.
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