Literature DB >> 10687407

Is causal induction based on causal power? Critique of Cheng (1997).

K Lober1, D R Shanks.   

Abstract

The authors empirically evaluate P. W. Cheng's (1997) power PC theory of causal induction. They reanalyze some published data taken to support the theory and show instead that the data are at variance with it. Then, they report 6 experiments in which participants evaluated the causal relationship between a fictitious chemical and DNA mutations. The power PC theory assumes that participants' estimates are based on the causal power p of a potential cause, where p is the contingency between the cause and the effect normalized by the base rate of the effect. Three of the experiments used a procedure in which causal information was presented trial by trial. For these experiments, the power PC theory was contrasted with the predictions of the probabilistic contrast model and the Rescorla-Wagner theory. For the remaining 3 experiments, a summary presentation format was employed to which only the probabilistic contrast model and the power PC theory are applicable. The power PC theory was unequivocally contradicted by the results obtained in these experiments, whereas the other 2 theories proved to be satisfactory.

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Mesh:

Year:  2000        PMID: 10687407     DOI: 10.1037/0033-295x.107.1.195

Source DB:  PubMed          Journal:  Psychol Rev        ISSN: 0033-295X            Impact factor:   8.934


  20 in total

Review 1.  Assessing power PC.

Authors:  Lorraine G Allan
Journal:  Learn Behav       Date:  2003-05       Impact factor: 1.986

2.  A dual-process model of belief and evidence interactions in causal reasoning.

Authors:  Jonathan A Fugelsang; Valerie A Thompson
Journal:  Mem Cognit       Date:  2003-07

3.  Causal judgment from contingency information: a systematic test of the pCI rule.

Authors:  Peter A White
Journal:  Mem Cognit       Date:  2004-04

4.  Extinction of conditioned inhibition through nonreinforced presentation of the inhibitor.

Authors:  Klaus G Melchers; Susann Wolff; Harald Lachnit
Journal:  Psychon Bull Rev       Date:  2006-08

5.  Models of covariation-based causal judgment: a review and synthesis.

Authors:  José C Perales; David R Shanks
Journal:  Psychon Bull Rev       Date:  2007-08

Review 6.  Comparing associative, statistical, and inferential reasoning accounts of human contingency learning.

Authors:  Oskar Pineño; Ralph R Miller
Journal:  Q J Exp Psychol (Hove)       Date:  2007-03       Impact factor: 2.143

7.  Accounting for occurrences: an explanation for some novel tendencies in causal judgment from contingency information.

Authors:  Peter A White
Journal:  Mem Cognit       Date:  2009-06

8.  The meaning and computation of causal power: comment on Cheng (1997) and Novick and Cheng (2004).

Authors:  Christian C Luhmann; Woo-Kyoung Ahn
Journal:  Psychol Rev       Date:  2005-07       Impact factor: 8.934

Review 9.  Contiguity and covariation in human causal inference.

Authors:  Marc J Buehner
Journal:  Learn Behav       Date:  2005-05       Impact factor: 1.986

10.  Surprise and change: variations in the strength of present and absent cues in causal learning.

Authors:  Edward A Wasserman; Leyre Castro
Journal:  Learn Behav       Date:  2005-05       Impact factor: 1.986

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