Probabilistic inversion in priority setting of emerging zoonoses

Dorota Kurowicka, Catalin Bucura, Roger Cooke, Arie Havelaar

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

This article presents methodology of applying probabilistic inversion in combination with expert judgment in priority setting problem. Experts rank scenarios according to severity. A linear multi-criteria analysis model underlying the expert preferences is posited. Using probabilistic inversion, a distribution over attribute weights is found that optimally reproduces the expert rankings. This model is validated in three ways. First, consistency of expert rankings is checked, second, a complete model fitted using all expert data is found to adequately reproduce observed expert rankings, and third, the model is fitted to subsets of the expert data and used to predict rankings in out-of-sample expert data.
Original languageEnglish
Pages (from-to)715-723
Number of pages9
JournalRisk Analysis
Volume30
Issue number5
Early online date15 Mar 2010
DOIs
Publication statusPublished - May 2010

    Fingerprint

Keywords

  • expert judgment
  • priority setting
  • probabilistic inversion
  • zoonoses

Cite this