Bayesian extensions of the Tobit model for analyzing measures of health status
Bayesian extensions of the Tobit model for analyzing measures of health status
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DOI：
10.1177/02729890222063035
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发表时间：
2002-03-01
影响因子：
3.6
通讯作者：
Austin, PC
中科院分区：
文献类型：
--
作者：
Austin, PC
自我报告的健康状况通常使用效用指数来衡量，效用指数提供旨在总结个人健康状况的分数。健康状况的测量可能会受到上限效应的影响。研究人员经常希望研究健康决定因素与健康状况衡量标准之间的关系。在本文中，经典 Tobit 模型的贝叶斯扩展用于研究健康状况和健康预测因子之间的关系。作者检查了健康状况的条件分布为正态或对数正态的模型，并允许同方差和异方差。然后使用贝叶斯因子将给定模型的证据与竞争模型的证据进行比较。作者发现了非常有力的证据，表明健康公用事业指数的分布以年龄、性别为条件。与竞争模型相比，收入充足性和慢性病数量正常，但方差不均匀。
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.