Multiple imputation with multivariate imputation by chained equation (MICE) package. - National Genomics Data Center (CNCB-NGDC)

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Multiple imputation with multivariate imputation by chained equation (MICE) package.

Zhongheng Zhang

Author Information

Zhongheng Zhang: Department of Critical Care Medicine, Jinhua Municipal Central Hospital, Jinhua Hospital of Zhejiang University, Jinhua 321000, China.

PMID: 26889483 DOI: 10.3978/j.issn.2305-5839.2015.12.63

Multiple imputation (MI) is an advanced technique for handing missing values. It is superior to single imputation in that it takes into account uncertainty in missing value imputation. However, MI is underutilized in medical literature due to lack of familiarity and computational challenges. The article provides a step-by-step approach to perform MI by using R multivariate imputation by chained equation (MICE) package. The procedure firstly imputed m sets of complete dataset by calling MICE() function. Then statistical analysis such as univariate analysis and regression model can be performed within each dataset by calling with() function. This function sets the environment for statistical analysis. Lastly, the results obtained from each analysis are combined by using pool() function.

Big-data clinical trial R imputed complete dataset multiple imputation (MI) multivariate imputation by chained equation (MICE) package

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Journal Article

Foetal ultrasound measurement imputations based on growth curves versus multiple imputation chained equation (MICE).Multilevel multiple imputation: A review and evaluation of joint modeling and chained equations imputation.Multiple imputation using chained equations: Issues and guidance for practice.Multiple imputation for time series data with Amelia package.Data integration of National Dose Registry and survey data using multivariate imputation by chained equations.Correction: Data integration of National Dose Registry and survey data using multivariate imputation by chained equations.Method for Incomplete and Imbalanced Data Based on Multivariate Imputation by Chained Equations and Ensemble Learning.Multiple imputation for missing data: fully conditional specification versus multivariate normal imputation.Multiple imputation by chained equations: what is it and how does it work?SuperMICE: An Ensemble Machine Learning Approach to Multiple Imputation by Chained Equations.

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