Department of Statistics

Recent Instructors Bloomfield, Peter Davidian, Marie	ST 732	Applied Longitudinal Data Analysis
	Course Description To intruduce students to statical models and methods for the analysis of longitudinal data, ie. data collected repeatedly on experimental units over time (or other conditions.) Course Syllabus Preliminaries Introduction Review of matrix algebra Random vectors, multivariate normal distribution, review of linear regression Introduction to modeling longitudinal data, exploring covariance structure Classical methods for normally distributed, balance repeated measurements. Univariate repeated measures analysis of variance Multivariate repeated measures analysis of variance Drawbacks and limitations of classical methods Methods for normally distributed, unbalanced repeated measurements: General linear models and models of correlation Random coefficient models Linear mixed effects models Methods for non-normally distributed, unbalanced data General linear models and models for correlation Random coefficient models Linear mixed effects models Advanced topics (brief overview) Generalized linear mixed effects models Nonlinear mixed effects models Missing data mechansims Course Prerequisites ST 512 Course Corequisites None Recent Textbooks None