Comparison for alternative imputation methods for ordinal data : conference proceedings

In this paper, we compare alternative missing imputation methods in the presence of ordinal data, in the framework of CUB (combination of uniform and (shifted) binomial random variable) models. Single and multiple imputation methods are considered, as well as univariate and multivariate approaches. The rst step consists of running a simulation study designed by varying the parameters of the CUB model, in order to consider and compare CUB models as well as other methods of missing imputation. We use real datasets on which to base the comparison between our approach and some general methods of missing imputation for various missing data patterns