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Multiple imputation for categorical time series

Author

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  • Brendan Halpin

    (University of Limerick)

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. Copyright 2016 by StataCorp LP.

Suggested Citation

  • Brendan Halpin, 2016. "Multiple imputation for categorical time series," Stata Journal, StataCorp LP, vol. 16(3), pages 590-612, September.
    • Handle: RePEc:tsj:stataj:v:16:y:2016:i:3:p:590-612
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    Citations

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    Cited by:

    1. Gao, Ni & Ryan, Mandy & Krucien, Nicolas & Robinson, Suzanne & Norman, Richard, 2020. "Paid work, household work, or leisure? Time allocation pathways among women following a cancer diagnosis," Social Science & Medicine, Elsevier, vol. 246(C).
    2. Dolores Sesma Carlos & Michel Oris & Jan Kok, 2022. "Coping with ageing: An historical longitudinal study of internal return migrations later in life in the Netherlands," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 46(27), pages 767-808.
    3. Marcel Raab & Anette Fasang & Moritz Hess, 2018. "Pathways to death: The co-occurrence of physical and mental health in the last years of life," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(53), pages 1619-1634.
    4. Raab, Marcel & Fasang, Anette Eva & Hess, Moritz, 2018. "Pathways to death: The co-occurrence of physical and mental health in the last years of life," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 38, pages 1619-1634.
    5. Liao, Tim F. & Bolano, Danilo & Brzinsky-Fay, Christian & Cornwell, Benjamin & Fasang, Anette Eva & Helske, Satu & Piccarreta, Raffaella & Raab, Marcel & Ritschard, Gilbert & Struffolino, Emanuela & S, 2022. "Sequence analysis: Its past, present, and future," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 107, pages 1-1.

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