title: The prevention and handling of the missing data.
abstract: Even in a well-designed and controlled study, missing data occurs in almost all research. Missing data can reduce the statistical power of a study and can produce biased estimates, leading to invalid conclusions. This manuscript reviews the problems and types of missing data, along with the techniques for handling missing data. The mechanisms by which missing data occurs are illustrated, and the methods for handling the missing data are discussed. The paper concludes with recommendations for the handling of missing data.
authors.affiliation: Department of Anesthesiology and Pain Medicine, Chung-Ang Universtiy College of Medicine, Seoul, Korea.
authors.forename: Hyun
authors.initials: H
authors.lastname: Kang
keywords: Expectation-Maximization; Imputation; Missing data; Sensitivity analysis