Multiple imputation (MI) is a method for repairing and analyzing data with missing values. MI replaces missing values with a sample of random values drawn from an imputation model. The most popular ...
While electronic health records present a rich and promising data source for observational research, they are highly susceptible to missing data. For settings like these, Seaman et al. (Biometrics 68 ...
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