The chapter sets out the aims of the book, the approach, what is covered in the book and what is not. The book starts by introducing several different variations of the basic linear model analysis (analysis of variance, linear regression, analysis of covariance, etc). Then two extensions are introduced: generalized linear models (for data with non-normal distributions) and mixed-effects models (for data with multiple levels and a hierarchical structure). The book ends by combining these two extensions into generalized linear mixed-effects models. To allow a learning-by-doing approach the R code necessary to perform the basic analysis is embedded in the text along with the key output from R.
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