TY - JOUR

T1 - The Relation between Probability and Evidence Judgment

T2 - An Extension of Support Theory

AU - Chen Idson, Lorraine

AU - Krantz, David H.

AU - Osherson, Daniel

AU - Bonini, Nicolao

N1 - Funding Information:
*Research in this paper was partly supported by NSF grants SBR-9818849 to D. H. Krantz and IIS-9978135 to D. Osherson.

PY - 2001

Y1 - 2001

N2 - We propose a theory that relates perceived evidence to numerical probability judgment. The most successful prior account of this relation is Support Theory, advanced in Tversky and Koehler (1994). Support Theory, however, implies additive probability estimates for binary partitions. In contrast, superadditivity has been documented in Macchi, Osherson, and Krantz (1999), and both sub- and superadditivity appear in the experiments reported here. Nonadditivity suggests asymmetry in the processing of focal and nonfocal hypotheses, even within binary partitions. We extend Support Theory by revising its basic equation to allow such asymmetry, and compare the two equations' ability to predict numerical assessments of probability from scaled estimates of evidence for and against a given proposition. Both between- and within-subject experimental designs are employed for this purpose. We find that the revised equation is more accurate than the original Support Theory equation. The implications of asymmetric processing on qualitative assessments of chance are also briefly discussed.

AB - We propose a theory that relates perceived evidence to numerical probability judgment. The most successful prior account of this relation is Support Theory, advanced in Tversky and Koehler (1994). Support Theory, however, implies additive probability estimates for binary partitions. In contrast, superadditivity has been documented in Macchi, Osherson, and Krantz (1999), and both sub- and superadditivity appear in the experiments reported here. Nonadditivity suggests asymmetry in the processing of focal and nonfocal hypotheses, even within binary partitions. We extend Support Theory by revising its basic equation to allow such asymmetry, and compare the two equations' ability to predict numerical assessments of probability from scaled estimates of evidence for and against a given proposition. Both between- and within-subject experimental designs are employed for this purpose. We find that the revised equation is more accurate than the original Support Theory equation. The implications of asymmetric processing on qualitative assessments of chance are also briefly discussed.

KW - Evidence judgment

KW - Probability judgment

KW - Subaddivity

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U2 - 10.1023/A:1011131017766

DO - 10.1023/A:1011131017766

M3 - Article

AN - SCOPUS:0041783474

VL - 22

SP - 227

EP - 249

JO - Journal of Risk and Uncertainty

JF - Journal of Risk and Uncertainty

SN - 0895-5646

IS - 3

ER -