The MI procedure performs multiple imputation of missing data. Missing values are an issue in a substantial number of statistical analyses. Most SAS statistical procedures exclude observations with any missing variable values from the analysis. These observations are called incomplete cases. Although analyzing only complete cases has the advantage of simplicity, the information contained in the incomplete cases is lost. This approach also ignores possible systematic differences between the complete cases and the incomplete cases, and the resulting inference might not be applicable to the population of all cases, especially with a small number of complete cases.
References in zbMATH (referenced in 1 article )
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- Horton, Nicholas J.; Lipsitz, Stuart R.; Parzen, Michael: A potential for bias when rounding in multiple imputation (2003)