Proceedings of the Annual Meeting of the Cognitive Science Society

The causal power theory of the probabilistic contrast model (or power PC theory) of causal induction (Cheng, in press) states that estimates of the causal importance of a candidate cause are determined by the covariation between the cause and the effect and the probability of the effect as indexed by the probability of the effect in the absence of the cause. In two causal induction experiments we tested predictions derived from the equations of the power PC theory. In Experiment 1, the power PC theory predicted equivalent causal estimates in conditions where the probability of the effect given the presence of the cause, P(effect | cause), equalled 1 and in conditions where P(effect | cause) equalled 0. Judgments, however, differed significantly within these conditions and conformed to the predictions of a simpler contingency model. These prediction failures might be attributable to the particular values of P(effect | cause), and thus Experiment 2 set this probability to values other than 1 or 0. Causal judgments again disconfirmed the predictions of the power PC theory and this time significantly failed to conform to the predictions of a simple contingency model.