Multiple imputation for categorical time series
Brendan Halpin
Department of Sociology
University of Limerick
Limerick, Ireland
[email protected]
|
Abstract. 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.
View all articles by this author:
Brendan Halpin
View all articles with these keywords:
mict_impute, mict_prep, mict_model_gap, mict_model_initial, mict_model_terminal, multiple imputation, categorical time series
Download citation: BibTeX RIS
Download citation and abstract: BibTeX RIS
|
