Linear mixed effects models

When to choose mixed-effects models, how to determine fixed effects vs. random effects, and nested vs. crossed sampling designs. Requirements and assumptions of mixed-effects models, and how to evaluate them. How mixed-effects models can improve parameter estimation with partial pooling/shrinkage.