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Understanding conjunction effects in probability judgments: the role of implicit mental models
Author(s) -
Betsch Tilmann,
Fiedler Klaus
Publication year - 1999
Publication title -
european journal of social psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.609
H-Index - 111
eISSN - 1099-0992
pISSN - 0046-2772
DOI - 10.1002/(sici)1099-0992(199902)29:1<75::aid-ejsp916>3.0.co;2-f
Subject(s) - conjunction (astronomy) , psychology , representativeness heuristic , cognitive psychology , normative , psychology of reasoning , mental model , conditional probability , social psychology , cognition , statistics , mathematics , cognitive science , philosophy , physics , verbal reasoning , epistemology , astronomy , neuroscience
Subjective probability judgments often violate a normative principle in that the conjunction of two events is judged to be more likely than the probability of either of the two events occurring separately. Most previous explanations of these conjunction effects have assumed that probability judgments depend on some psychological relation (e.g. representativeness) between the constituents mentioned explicitly in the stimulus information. In contrast, the present approach highlights the fundamental role of implicitly inferred information. Participants are assumed to transform the explicit stimulus information into implicit mental models in their attempt to make sense of the experimental task. Probability judgments should then reflect the degree of activation of such a mental model in memory given a set of propositions, rather than the quantitative fit or likelihood of the propositions themselves. Two studies are reported which provide converging evidence for the proposed mental model approach. In the first study, using graded conjunctions of one to five propositions, probability judgments are shown to vary as a function of the activation of a mental model rather than the likelihood of the component events. In a second study, a priming procedure is employed to activate mental models that either fit an event conjunction or do not, leading to an increase or decrease of conjunction effects in probability judgment. Copyright © 1999 John Wiley & Sons, Ltd.