Understanding pooled subjective probability estimates

Decision makers often must pool probability estimates from multiple experts before making a choice. Such pooling sometimes improves accuracy and other times diagnosticity. This article uses a cognitive model of the judge and the decision maker's classification of the information to explain why. Given a very weak model of the judge, the important factor is the degree to which their information bases are independent. The article also relates this work to other models in the literature. © 2001 Elsevier Science B.V. All rights reserved.

[1]  Christian Genest,et al.  Modeling Expert Judgments for Bayesian Updating , 1985 .

[2]  Claudia González-Vallejo,et al.  Statement Verification: A Stochastic Model of Judgment and Response. , 1994 .

[3]  Rami Zwick,et al.  Comparing the calibration and coherence of numerical and verbal probability judgments , 1993 .

[4]  D. M. Green,et al.  Signal detection theory and psychophysics , 1966 .

[5]  R. Cooke.  Experts in Uncertainty: Opinion and Subjective Probability in Science , 1991 .

[6]  I. Erev,et al.  The effect of explicit probabilities on decision weights and on the reflection effect , 1993 .

[7]  R. L. Winkler,et al.  Unanimity and compromise among probability forecasters , 1990 .

[8]  I. Erev,et al.  Simultaneous Over- and Underconfidence: The Role of Error in Judgment Processes. , 1994 .

[9]  G. Brier,et al.  External correspondence: Decompositions of the mean probability score , 1982 .

[10]  D. Budescu,et al.  Averaging probability judgments: Monte Carlo analyses of asymptotic diagnostic value , 2001 .

[11]  Christian Genest,et al.  Combining Probability Distributions: A Critique and an Annotated Bibliography , 1986 .

[12]  Robert L. Winkler,et al.  Expert resolution , 1986 .

[13]  A. H. Murphy.  A New Vector Partition of the Probability Score , 1973 .

[14]  Claudia González-Vallejo,et al.  Statement Verification: A Stochastic Model of Judgment and Response. , 1994 .

[15]  Peter A. Morris,et al.  An Axiomatic Approach to Expert Resolution , 1983 .

[16]  D. P. Gaver,et al.  Combining Information: Statistical Issues and Opportunities for Research , 1993 .

[17]  H Gu,et al.  The effects of averaging subjective probability estimates between and within judges. , 2000, Journal of experimental psychology. Applied.

[18]  R. Clemen.  Combining forecasts: A review and annotated bibliography , 1989 .

[19]  N. Etemadi,et al.  On the laws of large numbers for nonnegative random variables , 1983 .

[20]  A. Tversky,et al.  Support theory: A nonextensional representation of subjective probability. , 1994 .

[21]  Stephen K. McNees.  The uses and abuses of ‘consensus’ forecasts , 1992 .

[22]  A. Diederich,et al.  Evaluating and Combining Subjective Probability Estimates , 1997 .