Applied Generalized Linear Mixed Models in R

Preface

Before you start

Generalized linear mixed models (GLMM) are not easy. Two issues are combined here: (a) the dependency of observations and (b) the non-normal distribution of the response. If you are not familiar with how to deal with (a), we suggest that you start with mastering that part. The companion for this text that dives into general mixed models can be found here

In the remainder of this text we will focus on issue (b). In the situation of full independence of the observations (issue (a) is absent), we could use generalized linear models. We stated earlier that in life sciences and environmental sciences, the assumption of independence is nearly always violated. It is justified to aim immediately for the generalized mixed linear models, combining solutions to (a) and (b). Yet, most of our attention will go to the non-normality, and for explaining these models we will in the beginning even ignore issue (b).