Asymptotic judgment of cause in a relative validity paradigm

We report three experiments in which we tested asymptotic and dynamic predi ctions of the Rescorla-Wagner (R-W) model and the asymptotic predictions of Cheng's probabilistic contrast model (PCM) concerning judgments of causali ty when there are two possible causal candidates. We used a paradigm in whi ch the presence of a causal candidate that is highly correlated with an eff ect influences judgments of a second, moderately correlated or uncorrelated cause. In Experiment 1, which involved a moderate outcome density, judgmen ts of a moderately positive cause were attenuated when it was paired with e ither a perfect positive or perfect negative cause. This attenuation was ro bust over a large set of trials but was greater when the strong predictor w as positive. In Experiment 2, in which there was a low overall density of o utcomes, judgments of a moderately correlated positive cause were elevated when this cause was paired with a perfect negative causal candidate. This e levation 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 pred ictions of three theoretical models of causal judgments are considered. Bot h the R-W model and Cheng's PCM accounted for some but not all aspects of t he data Pearce's model of stimulus generalization accounts far a greater pr oportion of the data.