Maximum likelihood multiple imputation: Faster, more efficient imputation without posterior draws

Multiple imputation (MI) is a popular 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 form of MI, which we call posterior draw multiple imputation (PDMI), draws the parameters of the imputation model from a Bayesian posterior distribution. The advantage of PDMI is that it suppo…