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Multiple imputation using chained equations: Issues and guidance for practice

2010/11/30 by Ian R. White, Patrick Royston, Angela M. Wood +1 · 93 citations
Mathematics · #Advanced Causal Inference Techniques #Statistical Methods and Bayesian Inference #Statistical Methods in Clinical Trials

paper · doi:10.1002/sim.4067

openalex publication_date 2010/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Abstract

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.

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