The course emphasizes advanced experimental designs employed in biomedical research. It covers a variety of advanced ANOVA and regression topics such as block designs, repeated measures design, mixed effects models, analysis of missing data and model diagnostics and shows how these are applied to a variety of experimental designs. Mixed effect models will include: Gaussian linear mixed models (LMM), generalized linear mixed models (GLMM), and finite normal mixture models. Students should be familiar with the basic notions of random variables, statistical inference, multiple regression modeling and matrix algebra. The focus is on underlying statistical theory and applications. Familiarity with statistical software such as SAS, R, or STATA is expected.
BMTRY 701, 707