How to Elicit Many Probabilities

TL;DR

This paper introduces a new probability elicitation method for Bayesian networks that combines transcription and verbal-numerical scales, enabling experts to efficiently provide many probabilities in complex influence diagrams.

Contribution

The paper presents a novel elicitation technique that improves efficiency and ease of gathering numerous probabilities from domain experts in Bayesian network construction.

Findings

The new method allows rapid elicitation of many probabilities.

It combines transcription with verbal-numerical scales for assessments.

Proven effective in a complex influence diagram for cancer treatment.

Abstract

In building Bayesian belief networks, the elicitation of all probabilities required can be a major obstacle. We learned the extent of this often-cited observation in the construction of the probabilistic part of a complex influence diagram in the field of cancer treatment. Based upon our negative experiences with existing methods, we designed a new method for probability elicitation from domain experts. The method combines various ideas, among which are the ideas of transcribing probabilities and of using a scale with both numerical and verbal anchors for marking assessments. In the construction of the probabilistic part of our influence diagram, the method proved to allow for the elicitation of many probabilities in little time.