Covers statistical methods for the analysis of missing data, including likelihood-based, weighted GEE, multiple imputation, and Bayesian approaches. Uses computational tools such as EM algorithm and Gibbs' sampler. Covers both ignorable and non-ignorable missing-data mechanisms as well as cross-sectional and longitudinal study designs. Primarily uses data arising from epidemiologic studies.
Offered: jointly with EPI 531; Winter
BIOST 531
BIOST 531 Statistical Methods for Analysis with Missing Data
Past syllabus: 2019_WIN_BIOST_531_SadinleM.pdf135.51 KB