Literature DB >> 15832629

Judging relationships between events: how do we do it?

Lorraine G Allan1, Jason M Tangen.   

Abstract

A decade ago, Allan (1993) concluded that associative models provided the best account of data generated in tasks that require human observers to judge the relationship between binary events. In the intervening years, new data have been reported that provide evidence for higher-order processes. Some have argued that these new data pose a serious threat to the viability of the associative account. The purpose of the present paper is to review this evidence and to assess the severity of this threat.

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Year:  2005        PMID: 15832629     DOI: 10.1037/h0087456

Source DB:  PubMed          Journal:  Can J Exp Psychol        ISSN: 1196-1961


  5 in total

1.  A signal detection analysis of contingency data.

Authors:  Lorraine G Allan; Shepard Siegel; Jason M Tangen
Journal:  Learn Behav       Date:  2005-05       Impact factor: 1.986

Review 2.  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

3.  The "lunching" effect: pigeons track motion towards food more than motion away from it.

Authors:  Felipe Cabrera; Federico Sanabria; David Shelley; Peter R Killeen
Journal:  Behav Processes       Date:  2009-07-08       Impact factor: 1.777

4.  The spatiotemporal distinctiveness of direct causation.

Authors:  Michael E Young; Steven Sutherland
Journal:  Psychon Bull Rev       Date:  2009-08

5.  Associative foundation of causal learning in rats.

Authors:  Cody W Polack; Bridget L McConnell; Ralph R Miller
Journal:  Learn Behav       Date:  2013-03       Impact factor: 1.986

  5 in total

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