Brunswikian and Thurstonian Origins of Bias in Probability Assessment: On the Interpretation of Stochastic Components of Judgment

Uppsala University, SwedenABSTRACTIn this paper the Brunswikian framework provided by the theory of ProbabilisticMental Models (PMM), and other theoretical stances inspired by probabilisticfunctionalism, is combined with the Thurstonian notion of a stochastic com-ponent of judgment. We review data from 25 tasks with representative selection ofitems collected in our laboratory. Over/underconfidence is close to zero in mostdomains, but there is a moderate hard–easy e•ect across task domains that isinconsistent with the original assumptions of the Brunswikian framework. Thebinomial model modifies PMM-theory by allowing for sampling error in theprocess of learning the ecological probabilities and the response-error model takeserror in the process of overt probability assessment into account. Both modelspredict a moderate hard–easy e•ect across task environments that di•er indi†culty or predictability, but it is also demonstrated that the two interpretationsof random error lead to di•erent predictions. The response error model predictsformat dependence, with more overconfidence in full-range than in half-rangeassessment, and the phenomenon is illustrated with empirical data. It is proposedthat a model that combines the Brunswikian framework with both sampling errorand response error captures many of the important phenomena in the calibrationliterature. For illustrative purposes, a combined model with four parameters isfitted to empirical data suggesting good fit. #1997 by John Wiley & Sons, Ltd.