Missing Data and Multiple Imputation with Stata

In this talk Chuck Huber will introduce different kinds of mechanisms that lead to missing data such as missing at random (MAR), missing completely at random (MCAR), and missing not at random (MNAR). He then  will demonstrate how to use Stata's -mi- commands to impute missing data and fit models using the imputed datasets.