The document discusses mixed models, which contain both fixed and random effects. Fixed effects have all possible levels included in the study, while random effects are a random sample from the total population. The mixed model is represented as Y = Xβ + Zγ + ε, where β are fixed effects, X are fixed effect variables, Z are random effects, γ are random effect parameters, and ε is the error term. Mixed models can model both fixed and random effects, account for correlation in errors, and handle missing data. They provide correct standard errors compared to general linear models (GLMs). Model fitting involves likelihood ratio tests and information criteria to select the best fitting model.