Check Imputation Efficiency - How To Compare Data Frames? I try to evaluate several NA imputation methods with supervised approach: I clone my original data frame with no NAs, artifically insert NAs into the resulting Data Frame and apply imputations to the latter.

Now, I'd like to evaluate the imputations by comparing the imputed new DFs with the original one. I wonder what would be the best metod; is there any distance method for instance that I could apply to the original/imputed DF pairs?

(My DF contains only numeric data, but a solution that handles factor variables as well would be especially handy).
If we want to check the imputation efficiency, we should probably compute the performance for the imputed values only. Indeed, the performance depends on the percentage of missing values.