Missing Data Methods

Catalog description

Recent developments in the analysis of data with missing cases. Topics covered include types of missingness (missing at random, missing completely at random and missing not at random), planned missingness designs, maximum likelihood, Bayesian and multiple imputation methods for dealing with missing data. Analyses for data that are not missing at random will also be covered briefly.