Kharroubi Samer A, Brazier John E, Roberts Jennifer, O'Hagan Anthony
Department of Mathematics, University of York, Heslington, York YO10 5DD, UK.
J Health Econ. 2007 May 1;26(3):597-612. doi: 10.1016/j.jhealeco.2006.09.002. Epub 2006 Oct 27.
This paper reports on the findings from applying a new approach to modelling health state valuation data. The approach applies a nonparametric model to estimate SF-6D health state utility values using Bayesian methods. The data set is the UK SF-6D valuation study where a sample of 249 states defined by the SF-6D (a derivative of the SF-36) was valued by a representative sample of the UK general population using standard gamble. The paper presents the results from applying the nonparametric model and comparing it to the original model estimated using a conventional parametric random effects model. The two models are compared theoretically and in terms of empirical performance. The paper discusses the implications of these results for future applications of the SF-6D and further work in this field.
本文报告了应用一种新方法对健康状态评估数据进行建模的研究结果。该方法应用非参数模型，通过贝叶斯方法估计SF-6D健康状态效用值。数据集为英国SF-6D评估研究，其中由SF-6D（SF-36的衍生版本）定义的249种状态样本，由英国普通人群的代表性样本采用标准博弈法进行了评估。本文展示了应用非参数模型的结果，并将其与使用传统参数随机效应模型估计的原始模型进行了比较。从理论和实证表现方面对这两种模型进行了比较。本文讨论了这些结果对SF-6D未来应用以及该领域进一步研究工作的启示。
