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

   
@article{ATM8847,
	author = {Zhongheng Zhang},
	title = {Multiple imputation with multivariate imputation by chained equation (MICE) package},
	journal = {Annals of Translational Medicine},
	volume = {4},
	number = {2},
	year = {2016},
	keywords = {},
	abstract = {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.},
	issn = {2305-5847},	url = {https://atm.amegroups.org/article/view/8847}
}