ABSTRACT
Two contingency judgment experiments are reported where one predictive cue was present on every trial of the task. This constant cue was paired with a second variable cue that was either positively correlated (Experiment 1) or negatively correlated with the outcome event (Experiment 2). Outcome base rate was independently varied in both experiments. Probabilistic contrasts could be calculated for the variable cue but not for the constant cue since the probability of the outcome occurring in the absence of the constant cue was undefined. Cheng & Holyoak's (1995) probabilistic contrast model therefore cannot uniquely specify the way in which the constant cue will be judged. In contrast, judgments of the constant cue were systematically influenced by the variable cue's contingency as well as by the outcome base rate. Specifically, judgments of the constant cue 1) were discounted when the variable cue was a positive predictor of the outcome but were enhanced when the variable cue was a negative predictor of the outcome, and 2) were proportional to the outcome base rate. These effects were anticipated by a connectionist network using the Rescorla-Wagner learning rule.
