How to Elicit Many Probabilities
This work addresses a bottleneck in building complex influence diagrams for domain experts, though it appears incremental as it combines existing ideas into a new method.
The authors tackled the problem of efficiently eliciting many probabilities for Bayesian belief networks in cancer treatment, and their new method enabled rapid probability elicitation with significant time savings.
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.