Liming Cai
Mark Hayward
Yasuhiko Saito
James Lubitz
Aaron Hagedorn
Eileen Crimmins

http://www.demographic-research.org/volumes/vol22/6/

doi:10.4054/DemRes.2010.22.6

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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.

Author's affiliation
Liming Cai
National Center for Health Statistics, United States of America
Mark Hayward
University of Texas at Austin, United States of America
Yasuhiko Saito
Nihon University, Japan
James Lubitz
National Center for Health Statistics, United States of America
Aaron Hagedorn
University of Southern California, United States of America
Eileen Crimmins
University of Southern California, United States of America

Keywords
bootstrap, health expectancy, multi-state life table, population aging

Word count (Main text)
7708

Other articles by the same author/authors (in Demographic Research)

	[20-19] Trends in healthy life expectancy in Japan: 1986 - 2004
	[3-9] Change in the Prevalence of Diseases Among Older Americans: 1984-1994

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