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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Modelling covariates for the SF-6D standard gamble health state preference data using a nonparametric Bayesian

Samer Kharroubi1, John E Brazier, Anthony O'Hagan

  • 1University of York, UK. sak503@york.ac.uk

Social Science & Medicine (1982)
|December 13, 2006
PubMed
Summary

Respondent characteristics influence health state values. A non-parametric Bayesian approach found age significantly impacts SF-6D values, with other factors having minimal effect on UK general population health state valuations.

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Area of Science:

  • Health Economics
  • Biostatistics
  • Psychometrics

Background:

  • Respondent characteristics are known to influence health state valuations.
  • Existing models may not fully capture the complex relationship between demographics and perceived health utility.

Purpose of the Study:

  • To apply a non-parametric Bayesian approach to estimate covariates in a model of SF-6D health state values.
  • To investigate the impact of various respondent characteristics on health state values derived from the SF-6D instrument.

Main Methods:

  • Utilized a non-parametric Bayesian method for covariate estimation.
  • Employed data from the UK SF-6D valuation study, involving 249 health states valued by the UK general population using standard gamble.
  • The model ensures that full health passes through unity and allows covariate impacts to vary by health state.

Main Results:

  • Age was identified as a significant covariate affecting SF-6D health state values.
  • Sex, class, education, employment, and physical functioning showed probable, but less pronounced, effects.
  • Other covariates had no discernible impact on the estimated health state values.

Conclusions:

  • Non-parametric Bayesian modeling offers advantages for predicting health state values across diverse populations.
  • While age is a key factor, adjusting for covariates had minimal impact on mean health state values in the UK sample.
  • Findings have implications for health policy and the application of the SF-6D in economic evaluations.