"Multiple Imputation for Categorical Variables in Multilevel Data" by Helani D. Kottage
Multiple Imputation (MI) is a technique that imputes a set of plausible values for each missing item using an imputation model. An imputation model predicts a value for the missing item given the observed data and should be compatible with any model that is fitted to the multiply imputed data which is known as the substantive analysis model. To hold the compatibility, the imputation model has to capture the complexities in the substantive analysis model such as the structure of the data set and complex terms (higher order, interaction) considering the type of incomplete variable and the number...
Source: uow.edu.au