Aggregating point estimates: A flexible modeling approach

Aggregating point estimates: A flexible modeling approach

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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: ,
Keywords: decision: studies, statistics: empirical, ecology
Abstract:

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.

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