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

Liming Cai, Eileen Crimmins, Yasuhiko Saito, Mark D. Hayward, James Lubitz and Aaron Hagedorn
Additional contact information
Liming Cai: National Center for Health Statistics
Eileen Crimmins: University of Southern California
Yasuhiko Saito: Nihon University
Mark D. Hayward: University of Texas at Austin
James Lubitz: National Center for Health Statistics
Aaron Hagedorn: University of Southern California

Demographic Research, 2010, vol. 22, issue 6, 129-158

Abstract: 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.

Keywords: population aging; bootstrap; multistate life tables; health expectancy (search for similar items in EconPapers)
JEL-codes: J1 Z0 (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:dem:demres:v:22:y:2010:i:6

DOI: 10.4054/DemRes.2010.22.6

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