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Multiple imputation using chained equations: Issues and guidance for practice
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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.
2010 John Wiley & Sons, Ltd.