A Bayesian approach to sensitivity analysis

James C. Felli*, Gordon B. Hazen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


Sensitivity analysis has traditionally been applied to decision models to quantify the stability of a preferred alternative to parametric variation. In the health literature, sensitivity measures have traditionally been based upon distance metrics, payoff variations, and probability measures. We advocate a new approach based on information value and argue that such an approach is better suited to address the decision-maker's real concerns. We provide an example comparing conventional sensitivity analysis to one based on information value. This article is a US government work and is in the public domain in the United States.

Original languageEnglish (US)
Pages (from-to)263-268
Number of pages6
JournalHealth Economics
Issue number3
StatePublished - May 1999


  • Bayesian decision theory
  • Economics of information
  • Statistical methods
  • The value of information

ASJC Scopus subject areas

  • Health Policy


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