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Estimation of multi-state life table functions and their variability from complex survey data using the SPACE Program


  • Liming Cai

    (National Center for Health Statistics)

  • Mark Hayward

    (University of Texas at Austin)

  • Yasuhiko Saito

    (Nihon University)

  • James Lubitz

    (National Center for Health Statistics)

  • Aaron Hagedorn

    (University of Southern California)

  • Eileen Crimmins

    (University of Southern California)


The multistate life table (MSLT) model is an important demographic method to document life cycle processes. In this study, we present the SPACE (Stochastic Population Analysis for Complex Events) program to estimate MSLT functions and their sampling variability. It has several advantages over other programs, including the use of microsimulation and the bootstrap method to estimate the sampling variability. Simulation enables researchers to analyze a broader array of statistics than the deterministic approach, and may be especially advantageous in investigating distributions of MSLT functions. The bootstrap method takes sample design into account to correct the potential bias in variance estimates.

Suggested Citation

  • Liming Cai & Mark Hayward & Yasuhiko Saito & James Lubitz & Aaron Hagedorn & Eileen Crimmins, 2010. "Estimation of multi-state life table functions and their variability from complex survey data using the SPACE Program," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 22(6), pages 129-158, January.
  • Handle: RePEc:dem:demres:v:22:y:2010:i:6

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    References listed on IDEAS

    1. Agnes Lievre & Nicolas Brouard & Christopher Heathcote, 2003. "The Estimation Of Health Expectancies From Cross-Longitudinal Surveys," Mathematical Population Studies, Taylor & Francis Journals, vol. 10(4), pages 211-248.
    2. Liming Cai & Nathaniel Schenker & James Lubitz, 2006. "Analysis of functional status transitions by using a semi-Markov process model in the presence of left-censored spells," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(4), pages 477-491.
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    Cited by:

    1. repec:spr:demogr:v:54:y:2017:i:6:d:10.1007_s13524-017-0622-y is not listed on IDEAS
    2. repec:spr:demogr:v:54:y:2017:i:3:d:10.1007_s13524-017-0583-1 is not listed on IDEAS
    3. Jennifer Van Hook & Claire Altman, 2013. "Using Discrete-Time Event History Fertility Models to Simulate Total Fertility Rates and Other Fertility Measures," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 32(4), pages 585-610, August.
    4. Dustin Brown & Mark Hayward & Jennifer Montez & Robert Hummer & Chi-Tsun Chiu & Mira Hidajat, 2012. "The Significance of Education for Mortality Compression in the United States," Demography, Springer;Population Association of America (PAA), vol. 49(3), pages 819-840, August.

    More about this item


    bootstrap; health expectancy; multistate life tables; population aging;

    JEL classification:

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


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