The performance of multiple imputation (MI) for missing data in Likert-type items assuming multivariate normality was assessed using simulation methods. MI was robust to violations of continuity and normality. With 30% of missing data, MAR conditions resulted in negatively biased correlations. With 50% missingness, all results were negatively biased.
Leite, Walter and Beretvas, S. Natasha
"The Performance of Multiple Imputation for Likert-type Items with Missing Data,"
Journal of Modern Applied Statistical Methods: Vol. 9
, Article 8.
Available at: http://digitalcommons.wayne.edu/jmasm/vol9/iss1/8