articleStatistics in MedicineNov 30, 2010Closed access

Multiple imputation using chained equations: Issues and guidance for practice

IRIan R. WhitePRPatrick RoystonAWAngela Wood

MRC Biostatistics Unit · MRC Clinical Trials Unit at UCL · +2 more institutions

PubMed
Indexed incrossrefpubmed

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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Authors

3

Topics & keywords

Topics
Keywords
  • Imputation (statistics)
  • Categorical variable
  • Computer science
  • Missing data
  • Data mining
  • Machine learning
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