This paper outlines a strategy to validate multiple imputation methods. Rubin's criteria for proper multiple imputation are the point of departure. We describe a simulation method that yields insight into various aspects of bias and efficiency of the imputation process. We propose a new method for creating incomplete data under a general Missing At Random (MAR) mechanism. Software implementing the validation strategy is available as a SAS/IML module. The method is applied to investigate the behavior of polytomous regression imputation for categorical data.

Missing data mechanism, Multiple imputation, Proper imputation, Simulation,
Statistica Neerlandica
Department of Medical Informatics

Brand, J.P.L, van Buuren, S, Groothuis-Oudshoorn, K, & Gelsema, E.S. (2003). A toolkit in SAS for the evaluation of multiple imputation methods. Statistica Neerlandica (Vol. 57, pp. 36–45). doi:10.1111/1467-9574.00219