Multiple imputation using chained equations: Issues and guidance for practice
Multiple imputation using chained equations: Issues and guidance for practice
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DOI：
10.1002/sim.4067
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发表时间：
2011-02-20
影响因子：
2
通讯作者：
Wood, Angela M.
中科院分区：
文献类型：
--
作者：
White, Ian R.;Royston, Patrick;Wood, Angela M.
链式方程多重插补是处理缺失数据的一种灵活实用的方法。我们描述了该方法的原理，并展示了如何估算分类和定量变量，包括偏态变量。我们给出了如何指定插补模型和需要多少插补的指导。我们描述了多重插补数据的实际分析，包括模型建立和模型检验。我们强调的方法的局限性，并讨论可能的陷阱。我们使用心理健康的数据集来说明这些想法，并给出Stata代码片段。版权所有（C）2010约翰威利父子有限公司
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 (C) 2010 John Wiley & Sons, Ltd.