The objective in model-based imputation is to find a predictive model for each target variable in the data set that contains missing values. The model is fitted on the observed data and subsequently used to generate imputations for the missing values. Several commonly-used imputation methods are special cases of model-based imputation; this includes mean imputation, ratio imputation, and regression imputation.
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