title: From covariation to causation: a test of the assumption of causal power.
abstract: How humans infer causation from covariation has been the subject of a vigorous debate, most recently between the computational causal power account (P. W. Cheng, 1997) and associative learning theorists (e.g., K. Lober & D. R. Shanks, 2000). Whereas most researchers in the subject area agree that causal power as computed by the power PC theory offers a normative account of the inductive process. Lober and Shanks, among others, have questioned the empirical validity of the theory. This article offers a full report and additional analyses of the original study featured in Lober and Shanks's critique (M. J. Buehner & P. W. Cheng, 1997) and reports tests of Lober and Shanks's and other explanations of the pattern of causal judgments. Deviations from normativity, including the outcome-density bias, were found to be misperceptions of the input or other artifacts of the experimental procedures rather than inherent to the process of causal induction.
authors: Department of Psychology, Cardiff University, Cardiff, Wales. BuehnerM@Cardiff.ac.uk
authors: Marc J
authors: MJ
authors: Buehner
authors: Patricia W
authors: PW
authors: Cheng
authors: Deborah
authors: D
authors: Clifford
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D015982:Bias; D015984:Causality; D006801:Humans; D007600:Judgment; D011337:Probability Learning; D051381:Rats; D012016:Reference Values; D014611:Vaccination / Q000706:statistics & numerical data