Article ID: | iaor199450 |
Country: | United States |
Volume: | 39 |
Issue: | 4 |
Start Page Number: | 501 |
End Page Number: | 514 |
Publication Date: | Apr 1993 |
Journal: | Management Science |
Authors: | Clemen Robert T., Winkler Robert L. |
Keywords: | decision: studies, statistics: empirical, ecology |
In many decision situations information is available from a number of different sources. Aggregating the diverse bits of information is an important aspect of the decision-making process but entails special statistical modeling problems in characterizing the information. Prior research in this area has relied primarily on the use of historical data as a basis for modeling the information sources. The authors develop a Bayesian framework that a decision maker can use to encode subjective knowledge about the information sources in order to aggregate point estimates of an unknown quantity of interest. This framework features a highly flexible environment for modeling the probabilistic nature and interrelationships of the information sources and requires straightforward and intuitive subjective judgments using proven decision-analysis assessment techniques. Analysis of the constructed model produces a posterior distribution for the quantity of interest. An example based on health risks due to ozone exposure demonstrates the technique.