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Bayesian Extensions of the Tobit Model for Analyzing Measures of Health Status

Author

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  • Peter C. Austin

    (Institute for Clinical Evaluative Sciences, North York, Ontario, Canada, and the Department of Public Health Sciences, University of Toronto, Toronto, Ontario, Canada)

Abstract

Self-reported health status is often measured using utility indices that provide a score intended to summarize an individual’s health. Measurements of health status can be subject to a ceiling effect. Frequently, researchers want to examine relationships between determinants of health and measures of health status. In this article, Bayesian extensions of the classical Tobit model are used to study the relationship between health status and predictors of health. The author examined models where the conditional distribution of health status was either normal or lognormal, and allowed for both homoscedasticity and heteroscedasticity. Bayes factors were then used to compare the evidence for a given model against that for a competing model. The author found very strong evidence that the distribution of the Health Utilities Index, conditional on age, gender, income adequacy, and number of chronic conditions, was normal with nonuniform variance, compared to the competing models.

Suggested Citation

  • Peter C. Austin, 2002. "Bayesian Extensions of the Tobit Model for Analyzing Measures of Health Status," Medical Decision Making, , vol. 22(2), pages 152-162, April.
    • Handle: RePEc:sae:medema:v:22:y:2002:i:2:p:152-162
    DOI: 10.1177/0272989X0202200212
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    References listed on IDEAS

    as
    1. Steven Wei, 1999. "A bayesian approach to dynamic tobit models," Econometric Reviews, Taylor & Francis Journals, vol. 18(4), pages 417-439.
    2. Barton H. Hamilton, 1999. "HMO selection and Medicare costs: Bayesian MCMC estimation of a robust panel data tobit model with survival," Health Economics, John Wiley & Sons, Ltd., vol. 8(5), pages 403-414, August.
    3. Kai, Li, 1998. "Bayesian inference in a simultaneous equation model with limited dependent variables," Journal of Econometrics, Elsevier, vol. 85(2), pages 387-400, August.
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    Cited by:

    1. Harindra C. Wijeysundera & George Tomlinson & Colleen M. Norris & William A. Ghali & Dennis T. Ko & Murray D. Krahn, 2011. "Predicting EQ-5D Utility Scores from the Seattle Angina Questionnaire in Coronary Artery Disease," Medical Decision Making, , vol. 31(3), pages 481-493, May.
    2. Shengxiang Sang & Wei Liao & Ning Kang & Xueyan Wu & Ze Hu & Xiaotian Liu & Hongjian Zhang & Chongjian Wang, 2024. "Health-related quality of life assessed by EQ-5D-5L and its determinants among rural adults: result from the Henan rural cohort study," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(1), pages 21-30, February.

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