Subjective Probability Assessment in Decision Analysis: Partition Dependence and Bias Toward the Ignorance Prior

  • Fox C
  • Clemen R
  • 107

    Readers

    Mendeley users who have this article in their library.
  • 71

    Citations

    Citations of this article.

Abstract

D ecision and risk analysts have considerable discretion in designing procedures for eliciting subjective proba-bilities. One of the most popular approaches is to specify a particular set of exclusive and exhaustive events for which the assessor provides such judgments. We show that assessed probabilities are systematically biased toward a uniform distribution over all events into which the relevant state space happens to be partitioned, so that probabilities are " partition dependent. " We surmise that a typical assessor begins with an " ignorance prior " distribution that assigns equal probabilities to all specified events, then adjusts those probabilities insufficiently to reflect his or her beliefs concerning how the likelihoods of the events differ. In five studies, we demonstrate partition dependence for both discrete events and continuous variables (Studies 1 and 2), show that the bias decreases with increased domain knowledge (Studies 3 and 4), and that top experts in decision analysis are susceptible to this bias (Study 5). We relate our work to previous research on the " pruning bias " in fault-tree assessment (e.g., Fischhoff et al. 1978) and show that previous explanations of pruning bias (enhanced availabil-ity of events that are explicitly specified, ambiguity in interpreting event categories, and demand effects) cannot fully account for partition dependence. We conclude by discussing implications for decision analysis practice.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • Craig R. Fox

  • Robert T. Clemen

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free