Assessing Probability with Multiple Individuals: Group Interaction Versus Mathematical Aggregation.
Abstract
The application of decision theory often involves assessing subjective probabilities and procedures for assessing them are quite well developed. But such procedures are based on assessments by a single person. Often multiple individuals are called on to provide the probabilistic judgments. Unanimity in judgments among the multiple individuals cannot be expected, thereby creating the problem of how to arrive at a single probability distribution that can be used in applying decision theory. Two general approaches to this problem exist. The individuals can interact as a group to reach a consensus, or the individual judgments can be mathematically aggregated to produce a single probability distribution. Each of these approaches has advantages and disadvantages. Group interaction allows the exchange of information, but may be susceptible to dominance by certain individuals or pressure for conformity. Mathematical aggregation is simple to use and ensures that a single distribution will result, but theoretical difficulties are encountered in specifying an appropriate aggregation model. Using several forms of group interaction and mathematical aggregation models, this research investigated the quality of probabilities produced by interaction versus mathematical models.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1978
- Accession Number
- ADA073363
Entities
People
- David Arden Seaver