Probabilistic sensitivity analysis and value of information analysis

Ciaran N. Kohli-Lynch*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

This chapter focuses on the assessment of economic model uncertainty using Bayesian methods. Different sources of uncertainty in economic modelling are introduced. Approaches to deal with these sources of uncertainty are described. In particular, it is shown that probabilistic sensitivity analysis can help quantify parametric uncertainty in an economic model. Value of information analysis can then be employed to estimate the potential benefits associated with reducing parametric uncertainty. The practical steps required to conduct probabilistic and value of information analysis with an existing model are discussed. These methods can be useful to researchers who seek to gather more generalizable data to inform future iterations of economic models.

Original languageEnglish (US)
Title of host publicationHandbook of Applied Health Economics in Vaccines
PublisherOxford University Press
Pages290-309
Number of pages20
ISBN (Electronic)9780191918544
ISBN (Print)9780192896087
DOIs
StatePublished - Jan 1 2023

Keywords

  • disease models
  • economic models
  • probabilistic sensitivity analysis
  • uncertainty
  • value of information analysis

ASJC Scopus subject areas

  • General Medicine

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