Focuses on mixed-effects models that are commonly used in L2 research. Topics covered include data structures in within-participants experiments and longitudinal studies, cross-random effects (by-participant and by-item), random-effects structures (random intercepts and slopes), growth curve models, sample size justifications, and generalized mixed-effects models for binary, count, and ordinal outcomes. Readings and examples will be drawn from SLA research. Proficiency in R is expected.