By the same authors

From the same journal

From the same journal

Modeling SF-6D Hong Kong standard gamble health state preference data using a nonparametric bayesian method

Research output: Contribution to journalArticlepeer-review

Published copy (DOI)

Author(s)

Department/unit(s)

Publication details

JournalValue in Health
DatePublished - 1 Sep 2013
Issue number6
Volume16
Pages (from-to)1032-1045
Original languageEnglish

Abstract

Objectives This article reports on the findings from applying a recently described approach to modeling health state valuation data and the impact of the respondent characteristics on health state valuations. The approach applies a nonparametric model to estimate a Bayesian six-dimensional health state short form (derived from short-form 36 health survey) health state valuation algorithm. Methods A sample of 197 states defined by the six-dimensional health state short form (derived from short-form 36 health survey)has been valued by a representative sample of the Hong Kong general population by using standard gamble. The article reports the application of the nonparametric model and compares it to the original model estimated by using a conventional parametric random effects model. The two models are compared theoretically and in terms of empirical performance. Results Advantages of the nonparametric model are that it can be used to predict scores in populations with different distributions of characteristics than observed in the survey sample and that it allows for the impact of respondent characteristics to vary by health state (while ensuring that full health passes through unity). The results suggest an important age effect with sex, having some effect, but the remaining covariates having no discernible effect. Conclusions The nonparametric Bayesian model is argued to be more theoretically appropriate than previously used parametric models. Furthermore, it is more flexible to take into account the impact of covariates.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations