Accession Number : ADA133172
Title : A Theory of Diagnostic Inference: Judging Causality.
Descriptive Note : Technical rept. no. 4,
Corporate Author : CHICAGO UNIV IL CENTER FOR DECISION RESEARCH
Personal Author(s) : Einhorn,Hillel J ; Hogarth,Robin M
PDF Url : ADA133172
Report Date : Aug 1983
Pagination or Media Count : 70
Abstract : Diagnostic inference is concerned with determining the causal process that produced a set of outcomes/results/symptoms. A model of causal reasoning within diagnosis is presented. We first propose that people use a sequential anchor-and-adjust strategy in discounting an explanation by alternatives. The amount of discounting depends on three factors: the plausibility of alternatives, the initial strength of the hypothesis, and a parameter reflecting the weight given to disconfirmatory evidence. It is then shown that the strength of a causal explanation is highly dependent on an implicit causal background (as in figure/ground relations), and on probabilistic factors called cues-to-causality. The cues considered are temporal order, contiguity, covariation, and similarity of cause and effect. A model for weighting and combining the cues is shown to account for much research in a wide range of fields. The three components of the theory are then tested in a series of experiments and the results are discussed with respect to: the factors that affect the discounting of explanations; issues in combining the cues-to-causality; problems in defining the causal background; and normative questions in assessing the quality of causal judgments.
Descriptors : *Judgement(Psychology), *Reasoning, *Decision theory, *Decision making, Psychophysics, Diagnosis(General), Statistical analysis, Hypotheses, Validation, Attention, Mathematical models, Probability
Subject Categories : Psychology
Distribution Statement : APPROVED FOR PUBLIC RELEASE