Models of covariation-based causal judgment: A review and synthesis |
| |
Authors: | José C Perales David R Shanks |
| |
Institution: | (1) Department of Psychology, McGill University, 1205 Dr Penfield Ave, H3A 1B1 Montreal, QC, Canada;(2) University College, London, England; |
| |
Abstract: | Causal judgment is assumed to play a central role in prediction, control, and explanation. Here, we consider the function
or functions that map contingency information concerning the relationship between a single cue and a single outcome onto causal
judgments. We evaluate normative accounts of causal induction and report the findings of an extensive meta-analysis in which
we used a cross-validation model-fitting method and carried out a qualitative analysis of experimental trends in order to
compare a number of alternative models. The best model to emerge from this competition is one in which judgments are based
on the difference between the amount of confirming and disconfirming evidence. A rational justification for the use of this
model is proposed. |
| |
Keywords: | |
本文献已被 PubMed SpringerLink 等数据库收录! |
|