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Statistical inference for discrete-time multistate models: asymptotic covariance matrices, partial age ranges, and group contrasts

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  • Daniel C. Schneider

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

This paper lays out several new asymptotic inference results for discrete-time multistate models. First, it derives asymptotic covariance matrices for the outcome statistics of conditional and/or state expectancies, mean age at first entry, and lifetime risk. It then discusses group comparisons of these outcome measures, which require the calculation of a joint covariance matrix of two or more results. Finally, new procedures are presented for the estimation of multistate models over a partial age range, and how these subrange calculations relate to the result that is obtained from the full age range of the model. All newly derived expressions are compared against bootstrap results in order to verify correctness of results and to assess performance.

Suggested Citation

  • Daniel C. Schneider, 2023. "Statistical inference for discrete-time multistate models: asymptotic covariance matrices, partial age ranges, and group contrasts," MPIDR Working Papers WP-2023-041, Max Planck Institute for Demographic Research, Rostock, Germany.
    • Handle: RePEc:dem:wpaper:wp-2023-041
    DOI: 10.4054/MPIDR-WP-2023-041
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    More about this item

    Keywords

    multi-state life tables; statistical analysis;

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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