MICT: multiple imputation for categorical time-series

Abstract

The MICT package provides a method for multiple imputation for categorical time-series data such as lifecourse or employment-status histories that preserves longitudinal consistency, using a monotonic series of imputations. It allows flexible imputation specifications, with a model appropriate to the target variable (mlogit, ologit etc.). Where transitions are substantially less frequent than once per time-unit, and where missingness tends to be consecutive (as is typical of lifecourse data), it produces imputations with better longitudinal consistency than mi impute or ice.