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Modelling covariates for the SF-6D standard gamble health state preference data using a nonparametric Bayesian method

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  • Kharroubi, Samer
  • Brazier, John E.
  • O'Hagan, Anthony

Abstract

It has long been recognised that respondent characteristics can impact on the values they give to health states. This paper reports on the findings from applying a non-parametric approach to estimate the covariates in a model of SF-6D health state 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 derivate of the SF-36) was valued by a sample of the UK general population using standard gamble. Advantages of the nonparametric model are that it can be used to predict scores in populations with different distributions of characteristics and that it allows for an impact to vary by health state (whilst ensuring that full health passes through unity). The results suggest an important age effect, with sex, class, education, employment and physical functioning probably having some effect, but the remaining covariates having no discernable effect. Adjusting for covariates in the UK sample made little difference to mean health state values. The paper discusses the implications of these results for policy.

Suggested Citation

  • Kharroubi, Samer & Brazier, John E. & O'Hagan, Anthony, 2007. "Modelling covariates for the SF-6D standard gamble health state preference data using a nonparametric Bayesian method," Social Science & Medicine, Elsevier, vol. 64(6), pages 1242-1252, March.
    • Handle: RePEc:eee:socmed:v:64:y:2007:i:6:p:1242-1252
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    References listed on IDEAS

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    1. Oliver, Adam, 2003. "The internal consistency of the standard gamble: tests after adjusting for prospect theory," LSE Research Online Documents on Economics 159, London School of Economics and Political Science, LSE Library.
    2. Samer A. Kharroubi & Anthony O'Hagan & John E. Brazier, 2005. "Estimating utilities from individual health preference data: a nonparametric Bayesian method," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 879-895, November.
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    6. Bleichrodt, Han, 2001. "Probability Weighting in Choice under Risk: An Empirical Test," Journal of Risk and Uncertainty, Springer, vol. 23(2), pages 185-198, September.
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    8. Menzel, Paul & Dolan, Paul & Richardson, Jeff & Olsen, Jan Abel, 2002. "The role of adaptation to disability and disease in health state valuation: a preliminary normative analysis," Social Science & Medicine, Elsevier, vol. 55(12), pages 2149-2158, December.
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    6. O'Hagan, A & Brazier, JE & Kharroubi, SA, 2007. "A comparison of United States and United Kingdom EQ-5D health states valuations using a nonparametric Bayesian method," MPRA Paper 29806, University Library of Munich, Germany.
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