title: Asymptotic judgment of cause in a relative validity paradigm.
abstract: We report three experiments in which we tested asymptotic and dynamic predictions of the Rescorla-Wagner (R-W) model and the asymptotic predictions of Cheng's probabilistic contrast model (PCM) concerning judgments of causality when there are two possible causal candidates. We used a paradigm in which the presence of a causal candidate that is highly correlated with an effect influences judgments of a second, moderately correlated or uncorrelated cause. In Experiment 1, which involved a moderate outcome density, judgments of a moderately positive cause were attenuated when it was paired with either a perfect positive or perfect negative cause. This attenuation was robust over a large set of trials but was greater when the strong predictor was positive. In Experiment 2, in which there was a low overall density of outcomes, judgments of a moderately correlated positive cause were elevated when this cause was paired with a perfect negative causal candidate. This elevation was also quite robust over a large set of trials. In Experiment 3, estimates of the strength of a causal candidate that was uncorrelated with the outcome were reduced when it was paired with a perfect cause. The predictions of three theoretical models of causal judgments are considered. Both the R-W model and Cheng's PCM accounted for some but not all aspects of the data. Pearce's model of stimulus generalization accounts for a greater proportion of the data.
authors.affiliation: Department of Psychology, McGill University, Montreal, PQ, Canada. bakerandy@hebb.psych.mcgill.ca
authors.forename: A G
authors.initials: AG
authors.lastname: Baker
authors.forename: F
authors.initials: F
authors.lastname: Vallée-Tourangeau
authors.forename: R A
authors.initials: RA
authors.lastname: Murphy
mesh_terms: D000328:Adult; D015984:Causality; D003210:Concept Formation; D005260:Female; D006801:Humans; D007600:Judgment; D008297:Male; D008960:Models, Psychological; D011337:Probability Learning