The Relation between Probability and Evidence Judgment: An Extension of Support Theory

Lorraine Chen Idson, David H. Krantz, Daniel Osherson, Nicolao Bonini

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)227-249
Number of pages23
JournalJournal of Risk and Uncertainty
Volume22
Issue number3
DOIs
StatePublished - Jan 1 2001

All Science Journal Classification (ASJC) codes

  • Accounting
  • Finance
  • Economics and Econometrics

Keywords

  • Evidence judgment
  • Probability judgment
  • Subaddivity

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