Direct Likelihood Analysis and Multiple Imputation for Missing Item Scores in…

Multiple imputation (MI) has become a highly useful technique for handling missing values in many settings. In this article, the authors compare the performance of a MI model based on empirical Bayes techniques to a direct maximum likelihood analysis approach that is known to be robust in the presence of missing observations. Specifically, they focus on handling of missing item scores in multil…