A toolkit in SAS for the evaluation of multiple imputation methods

Jaap P.L. Brand, Stef van Buuren, Karin Groothuis-Oudshoorn, Edzard S. Gelsema

Research output: Contribution to journalArticleAcademicpeer-review

24 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)36-45
Number of pages10
JournalStatistica Neerlandica
Volume57
Issue number1
DOIs
Publication statusPublished - Feb 2003
Externally publishedYes

Keywords

  • multiple imputation
  • proper imputation
  • missing data mechanism
  • simulation

Cite this