Dealing with missing data: Part II

The main concepts of the maximum likelihood (ML) approach in dealing with missing data are introduced and simple numerical examples of the application of ML are presented. Differences between ML and other techniques of treating missing data are illustrated. The idea of multiple imputation (MI) approach is presented and illustrated as well.