This paper reports on the findings from the application of a recently reported approach to modelling health state valuation data. The approach applies a nonparametric model to estimate the revised version of the Health Utilities Index Mark 2 (HUI 2) health state valuation algorithm using Bayesian methods. The data set is the UK HUI 2 valuation study where a sample of 51 states defined by the HUI 2 was valued by a sample of the UK general population using standard gamble. The paper presents the results from applying the nonparametric model and compares these to the original model estimated using a conventional parametric random effects model. The two models are compared in terms of their predictive performance. The paper discusses the implications of these results for future applications of the HUI 2 and further work in this field
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