Causal judgement: use of different types of contingency information as confirmatory and disconfirmatory

In three experiments, participants made causal judgements from summary presentations of information about occurrences and non-occurrences of an effect in the presence and absence of possible causes. Participants' judgements could best be accounted for by the hypothesis that some were tending to use cell information in idiosyncratic ways: types of contingency information normatively regarded as confirmatory were sometimes treated as disconfirmatory and vice versa. In all three experiments, participants' judgements were better predicted by a model based on this evidence than by the probabilistic contrast model (Cheng and Novick, 1992) or the Power PC theory (Cheng, 1997).

[1]  D. Kuhn.  Children and adults as intuitive scientists. , 1989, Psychological review.

[2]  David R. Shanks,et al.  The Psychology of Associative Learning , 1995 .

[3]  David R. Shanks,et al.  Acquisition functions in contingency judgment , 1987 .

[4]  J. Smedslund.  THE CONCEPT OF CORRELATION IN ADULTS , 1963 .

[5]  D. Shanks,et al.  Human instrumental learning: a critical review of data and theory. , 1993, British journal of psychology.

[6]  Hal R. Arkes,et al.  Estimates of contingency between two dichotomous variables. , 1983 .

[7]  John R. Anderson,et al.  Causal inferences as perceptual judgments , 1995, Memory & cognition.

[8]  E. Wasserman.  Attribution of Causality to Common and Distinctive Elements of Compound Stimuli , 1990 .

[9]  D. Shanks.  On Similarities between Causal Judgments in Experienced and Described Situations , 1991 .

[10]  H. Shaklee,et al.  A rule analysis of judgments of covariation between events , 1980, Memory & cognition.

[11]  G. Chapman,et al.  Cue interaction in human contingency judgment , 1990, Memory & cognition.

[12]  Michael E. Young.  On the origin of personal causal theories , 1995, Psychonomic bulletin & review.

[13]  E. Wasserman,et al.  Cue competition in causality judgments: The role of manner of information presentation , 1993 .

[14]  E. Wasserman,et al.  Rating causal relations: Role of probability in judgments of response-outcome contingency. , 1993 .

[15]  F. Försterling,et al.  Models of covariation and attribution: How do they relate to the analogy of analysis of variance? , 1989 .

[16]  Harriet Shaklee,et al.  Methods of Assessing Strategies for Judging Covariation between Events. , 1983 .

[17]  Harriet Shaklee,et al.  Sources of error in judging event covariations: Effects of memory demands. , 1982 .

[18]  A. Lawson,et al.  Intellectual Development Beyond Elementary School VI: Correlational Reasoning , 1978 .

[19]  G. Chapman,et al.  Trial order affects cue interaction in contingency judgment. , 1991, Journal of experimental psychology. Learning, memory, and cognition.

[20]  L. J. Chapman,et al.  Genesis of popular but erroneous psychodiagnostic observations. , 1967, Journal of abnormal psychology.

[21]  L. Schauble,et al.  Belief revision in children: the role of prior knowledge and strategies for generating evidence. , 1990, Journal of experimental child psychology.

[22]  R. Sternberg,et al.  Evaluation of evidence in causal inference. , 1981 .

[23]  P. White.  The Understanding of Causation and the Production of Action , 1995 .

[24]  E. Wasserman,et al.  Judging interevent contingencies: Being right for the wrong reasons , 1986 .

[25]  Joel T. Johnson,et al.  Causal reasoning in the attribution of rare and common events. , 1994 .

[26]  P. Cheng,et al.  Causes versus enabling conditions , 1991, Cognition.

[27]  L. Ross,et al.  Human Inference: Strategies and Shortcomings of Social Judgment. , 1981 .

[28]  P. Cheng.  From covariation to causation: A causal power theory. , 1997 .

[29]  E. Wasserman,et al.  Assessment of an information integration account of contingency judgment with examination of subjective cell importance and method of information presentation. , 1993 .

[30]  J. Crocker.  Biased Questions in Judgment of Covariation Studies , 1982 .

[31]  Knowledge-based assumptions in causal attribution , 1992 .

[32]  C. Mckenzie.  The Accuracy of Intuitive Judgment Strategies: Covariation Assessment and Bayesian Inference , 1994, Cognitive Psychology.

[33]  H. M. Jenkins,et al.  JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES. , 1965, Psychological monographs.

[34]  Dawn Iacobucci,et al.  Analysis of Attribution Data: Theory Testing and Effects Estimation , 1990 .

[35]  H. M. Jenkins,et al.  The display of information and the judgment of contingency. , 1965, Canadian journal of psychology.

[36]  H. Kelley.  The processes of causal attribution. , 1973 .

[37]  Laura R. Novick,et al.  A probabilistic contrast model of causal induction. , 1990 .

[38]  E A Wasserman,et al.  Contributions of specific cell information to judgments of interevent contingency. , 1990, Journal of experimental psychology. Learning, memory, and cognition.

[39]  H. Kelley.  Attribution in social interaction. , 1987 .

[40]  Teresa M. Amabile,et al.  Judgment under uncertainty: Informal covariation assessment: Data-based versus theory-based judgments , 1982 .

[41]  P. Cheng,et al.  Covariation in natural causal induction. , 1992 .

[42]  C. Peterson.  Recognition of noncontingency. , 1980 .

[43]  G. A. Miller,et al.  Book Review Nisbett, R. , & Ross, L.Human inference: Strategies and shortcomings of social judgment.Englewood Cliffs, N.J.: Prentice-Hall, 1980. , 1982 .

[44]  E. Wasserman,et al.  Multiple Methods for Examining Biased Information Use in Contingency Judgments , 1993 .