Multiple Imputation Using Chained Equations (MICE)
*Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health 

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This workshop will discuss multiple imputation using chained equations (MICE), a flexible procedure for creating multiple imputations to handle missing data. MICE can handle many data complexities, such as bounds and survey skip patterns, and can be implemented in large datasets. After providing a brief introduction to missing data and multiple imputation in general, this workshop will discuss the MICE method and provide references for software implementation.