Literature DB >> 19210088

The influence of virtual sample size on confidence and causal-strength judgments.

Mimi Liljeholm1, Patricia W Cheng.   

Abstract

The authors investigated whether confidence in causal judgments varies with virtual sample size--the frequency of cases in which the outcome is (a) absent before the introduction of a generative cause or (b) present before the introduction of a preventive cause. Participants were asked to evaluate the influence of various candidate causes on an outcome as well as to rate their confidence in those judgments. They were presented with information on the relative frequencies of the outcome given the presence and absence of various candidate causes. These relative frequencies, sample size, and the direction of the causal influence (generative vs. preventive) were manipulated. It was found that both virtual and actual sample size affected confidence. Further, confidence affected estimates of strength, but confidence and strength are dissociable. The results enable a consistent explanation of the puzzling previous finding that observed causal-strength ratings often deviated from the predictions of both of the 2 dominant models of causal strength.

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Year:  2009        PMID: 19210088     DOI: 10.1037/a0013972

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  4 in total

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2.  Individuals Who Believe in the Paranormal Expose Themselves to Biased Information and Develop More Causal Illusions than Nonbelievers in the Laboratory.

Authors:  Fernando Blanco; Itxaso Barberia; Helena Matute
Journal:  PLoS One       Date:  2015-07-15       Impact factor: 3.240

3.  Two heads are better than one, but how much? Evidence that people's use of causal integration rules does not always conform to normative standards.

Authors:  Miguel A Vadillo; Nerea Ortega-Castro; Itxaso Barberia; A G Baker
Journal:  Exp Psychol       Date:  2014

4.  Adapting to an Uncertain World: Cognitive Capacity and Causal Reasoning with Ambiguous Observations.

Authors:  Yiyun Shou; Michael Smithson
Journal:  PLoS One       Date:  2015-10-15       Impact factor: 3.240

  4 in total

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