Statistical Analysis with Missing Data

Course content

Problem of missing data; missing data patterns and mechanisms; single and multiple imputation methods; likelihood based inference; Bayesian simulation based inference; data augmentation; missing data handling for correlated, longitudinal, and clustered data; missing data analysis in SAS and R.