Mixed models have recently become one of the most important classes of linear and nonlinear models. Although such a topic is too advanced to be treated in this introductory book, it seemed fundamental to mention how mixed models can be used to analyze data from several important types of experiments that are widely prevalent in agricultural research. Six real-life examples are presented, relating to a split-plot design, a strip-plot design, a genotype experiment with subsampling, a genotype experiment with random blocks, a multiyear genotype experiment, and a multiyear experiment with a perennial crop. For these case studies, the use of the lme4 package is proposed, and the differences between fixed-effects model fitting and mixed model fitting are pointed out and discussed.