Prerequisites: graduate standing; or consent of instructor

Description: Topics include linear mixed effects models; generalized linear models; nonlinear mixed effects models; repeated measures; ANOVA/MANOVA; graphical data exploration; correlation structures; parameter estimation/testing inference; and model selection, diagnostics, and limitations.

Credit: May be taken Satisfactory (S) or No Credit (NC) with consent of instructor and graduate advisor.