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Researchers often face the problem of how to address missing data. Multiple imputation is a popular approach, with Multiple Imputation by Chained Equations (MICE) among the most common and flexible methods for execution. MICE iter- atively fits a predictive model for each variable with missing values, conditional on other variables in the data. In theory, any imputation model can be used to predict the missing values. However, if the predictive models are incorrectly specified, they may produce biased estimates of the imputed data, yield
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