A toolkit in SAS for the evaluation of multiple imputation methods
article
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. © VVS, 2003.
TNO Identifier
236948
ISSN
00390402
Source
Statistica Neerlandica, 57(1), pp. 36-45.
Pages
36-45
Files
To receive the publication files, please send an e-mail request to TNO Repository.