ABSTRACT
Creating plausible imputations is the most challenging activity in multiple imputation. Once we have the multiply imputed data, we can estimate the parameters of scientific interest from each of the m imputed datasets, but now without the need to deal with the missing data, as all data are now complete. These repeated analyses produce m results.
