Inferring causality assessments from predictive responses: cue interaction without cue competition.

The authors criticize the use of participants' predictive responses during a learning phase as a measure of causal assessments. Simulations demonstrate that a general aim to minimize error as required in the prediction task will produce results in accordance with those observed, in particular apparent cue interaction effects. It is argued that measures estimated from prediction responses do not reflect causal ratings, but are side-effects of learning explained by adaptation in strategy to changes in presented cell frequencies. The results are reinterpreted to be in line with a causal model view, not requiring dual processes or cue competition of lower level associative processes.