Active Life Expectancy from Annual Follow–Up Data with Missing Responses
Version of Record online: 25 MAY 2004
Volume 56, Issue 1, pages 244–248, March 2000
How to Cite
Izmirlian, G., Brock, D., Ferrucci, L. and Phillips, C. (2000), Active Life Expectancy from Annual Follow–Up Data with Missing Responses. Biometrics, 56: 244–248. doi: 10.1111/j.0006-341X.2000.00244.x
- Issue online: 25 MAY 2004
- Version of Record online: 25 MAY 2004
- Received August 1997. Revised May 1999. Accepted May 1999.
- Active life expectancy;
- Markov model;
Summary. Active life expectancy (ALE) at a given age is denned as the expected remaining years free of disability. In this study, three categories of health status are defined according to the ability to perform activities of daily living independently. Several studies have used increment-decrement life tables to estimate ALE, without error analysis, from only a baseline and one follow-up interview. The present work conducts an individual-level covariate analysis using a three-state Markov chain model for multiple follow-up data. Using a logistic link, the model estimates single-year transition probabilities among states of health, accounting for missing interviews. This approach has the advantages of smoothing subsequent estimates and increased power by using all follow-ups. We compute ALE and total life expectancy from these estimated single-year transition probabilities. Variance estimates are computed using the delta method. Data from the Iowa Established Population for the Epidemiologic Study of the Elderly are used to test the effects of smoking on ALE on all 5-year age groups past 65 years, controlling for sex and education.