dyestuff_SimpleLMM

In this vignette we describe the theory behind a type of statistical model called mixed-effects models and the practice of fitting and analyzing such models using the MixedModels package for Julia. These models are used in many different disciplines. Because the descriptions of the models can vary markedly between disciplines, we begin by describing what mixed-effects models are and by exploring a very simple example of one type of mixed model, the linear mixed model. This simple example allows us to illustrate the use of the MixedModels package for fitting such models and other functions for analyzing the fitted model. We also describe methods of assessing the precision of the parameter estimates and of visualizing the conditional distribution of the random effects, given the observed data.