Likelihood judgment plays a critical role in decisions that are made in almost all of life's domains. Often, people must judge the likelihood of one event when more than one alternative event is known to be possible (e.g., the likelihood that a patient has condition A rather than condition B, C, or D; the likelihood that a contract for a construction project will be awarded to bidder F rather than G or H; the likelihood that a friend is arriving on airline K rather than M or L). The proposed research will examine fundamental processes underlying such likelihood judgments. Recent research by the primary investigator suggests that judgments of likelihood are often mediated by a distinct comparison heuristic; such judgments are largely dependent upon a comparison between the strength of the evidence for the focal event and the strongest alternative event, rather than a weighing of the evidence for the focal event versus the aggregate of the evidence for all alternative events. The comparison heuristic is very efficient and generally produces reasonable judgments of likelihood. However, the heuristic can also underlie patterns of perceived likelihood that are not consistent with the normative dictates of standard probability theory. Nine experiments will investigate the nature, strength, and scope of the comparison heuristic. They will also examine how task conditions that vary under everyday judgment situations--time pressure, the type of response being solicited, and the quantifiability of the available evidence--influence likelihood judgments. The experiments will involve a wide range of paradigms and judgment types. Various methodological tools (e.g., manipulations to the distributions of alternative outcomes, process tracing) will allow for an assessment of the relative influence of deliberative versus heuristic processes within manipulated conditions of the experiments. This research should substantially advance the understanding of processes mediating judgments of likelihood as well as enhance researchers' abilities to predict judgments (and decisions and behaviors) that are based on perceptions of focal events that have multiple alternatives.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Robert E. O'Connor
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University of Iowa
Iowa City
United States
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