Tutorial in Biostatistics
Multiple imputation using chained equations: Issues and guidance for practice
Article first published online: 30 NOV 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 30, Issue 4, pages 377–399, 20 February 2011
How to Cite
White, I. R., Royston, P. and Wood, A. M. (2011), Multiple imputation using chained equations: Issues and guidance for practice. Statist. Med., 30: 377–399. doi: 10.1002/sim.4067
- Issue published online: 10 JAN 2011
- Article first published online: 30 NOV 2010
- Manuscript Accepted: 14 JUL 2010
- Manuscript Received: 3 SEP 2009
- missing data;
- multiple imputation;
- fully conditional specification
Multiple imputation by chained equations is a flexible and practical approach to handling missing data. We describe the principles of the method and show how to impute categorical and quantitative variables, including skewed variables. We give guidance on how to specify the imputation model and how many imputations are needed. We describe the practical analysis of multiply imputed data, including model building and model checking. We stress the limitations of the method and discuss the possible pitfalls. We illustrate the ideas using a data set in mental health, giving Stata code fragments. Copyright © 2010 John Wiley & Sons, Ltd.