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A toolkit in SAS for the evaluation of multiple imputation methods |
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| Authors: | Jaap PL Brand Stef van Buuren Karin Groothuis-Oudshoorn Edzard S Gelsema† |
| Institution: | Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, USA ;Department of Statistics, TNO Prevention and Health, Leiden, The Netherlands ;Department of Statistics, TNO Prevention and Health, Leiden, The Netherlands ;Department of Medical Informatics, Rotterdam, The Netherlands |
| Abstract: | 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. |
| Keywords: | multiple imputation proper imputation missing data mechanism simulation |