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Related Experiment Video

Updated: Jul 14, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Eliciting expert opinion for economic models: an applied example.

José Leal1, Sarah Wordsworth, Rosa Legood

  • 1Health Economics Research Centre, Department of Public Health, University of Oxford, Old Road Campus, Oxford, UK. jose.leal@dphpc.ox.ac.uk

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research
|May 30, 2007
PubMed
Summary

A new computer tool simplifies eliciting expert opinion for decision-analytic models when data is scarce. This practical approach improves uncertainty distribution assessment for model parameters.

Related Experiment Videos

Last Updated: Jul 14, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Area of Science:

  • Decision Analysis
  • Health Economics
  • Biostatistics

Background:

  • Expert opinion is crucial for decision-analytic modeling when data is unavailable.
  • Existing elicitation techniques can be complex and difficult to implement in practice.
  • A need exists for practical tools to gather expert judgment for model parameters.

Purpose of the Study:

  • To develop a user-friendly, computer-based tool for eliciting expert opinion.
  • To assess the shape of uncertainty distributions around individual model parameters.
  • To facilitate the incorporation of expert-derived uncertainty into decision-analytic models.

Main Methods:

  • A prepilot survey refined elicitation approaches for uncertainty distributions.
  • A survey instrument was developed for an applied clinical economic model.
  • Experts (cardiologists, geneticists, scientists) provided opinions on DNA testing for hypertrophic cardiomyopathy.

Main Results:

  • The developed tool was rated as easy to use by respondents.
  • A 50% response rate was achieved with logical and usable answers.
  • Graphical feedback in the software enhanced the elicitation process.
  • Obtained distributions were successfully integrated into a model for probabilistic sensitivity analysis.

Conclusions:

  • A practical gap exists between theoretical expert elicitation methods and applied decision-analytic modeling tools.
  • The developed computer-based tool offers a valuable solution for decision analysts.
  • This methodology can aid in deriving expert opinion for complex models.