Peer-Reviewed Journal Details
Mandatory Fields
Halpin, B
2016
December
Stata Journal
Multiple imputation for categorical time series
Published
()
Optional Fields
st0445 mict_impute mict_prep mict_model_gap mitt model initial mict_model_terminal multiple imputation categorical time series FULLY CONDITIONAL SPECIFICATION SEQUENCE-ANALYSIS MISSING VALUES WORK
16
590
612
The mict package provides a method for multiple imputation of categorical time-series data (such as life course 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 in individual units' data are substantially less frequent than one per period and where missingness tends to be consecutive (as is typical of life course data), mict produces imputations with better longitudinal consistency than mi impute or ice.
Grant Details