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Proceedings of the Annual Meeting of the Cognitive Science Society
We hypothesized that causal conditional reasoning reflects judgment of the conditional likelihood of causes and effects based on a probabilistic causal model of the scenario being judged. Although this proposal has much in common with Cummins' (1995) theory based on the number of disabling conditions and alternative causes, it takes more variables into account and therefore makes some differing predictions. To test this idea we collected judgments of the causal parameters of the conditionalsfatcat:mwrexlylivh47brg7cjqgfmibi