Introduction to Multiple Imputation

Abstract

Missing data is a common problem in clinical epidemiology research. Inappropriate handling of missing data leads to biased results. This paper explains the mechanisms of missing data and several methods for handling missing data. In particular, multiple imputation is a more valid approach than other methods. Therefore, this paper focuses on the assumptions and procedures for multiple imputation and describes its limitations.