Literature DB >> 27815818

Effects of outcome and trial frequency on the inverse base-rate effect.

Hilary J Don1, Evan J Livesey2.   

Abstract

The inverse base-rate effect is a bias in contingency learning in which participants tend to predict a rare outcome for a conflicting set of perfectly predictive cues. Although the effect is often explained by attention biases during learning, inferential strategies at test may also contribute substantially to the effect. In three experiments, we manipulated the frequencies of outcomes and trial types to determine the critical conditions for the effect, thereby providing novel tests of the reasoning processes that could contribute to it. The rare bias was substantially reduced when the outcomes were experienced at equal rates in the presence of predictive-cue frequency differences (Exp. 2), and when the predictive cues were experienced at equal rates in the presence of outcome frequency differences (Exp. 3). We also found a consistent common-outcome bias for novel cue compounds. The results indicate the importance of both cue and outcome frequencies to the inverse base-rate effect, and reveal a combination of necessary conditions that are not well captured by appealing to inferential strategies at test. Although both attention-based and inferential theories explain some aspects of these data, no existing theory fully accounts for these effects of relative novelty.

Entities:  

Keywords:  Contingency learning; Cue competition; Inferential reasoning; Inverse base-rate effect

Mesh:

Year:  2017        PMID: 27815818     DOI: 10.3758/s13421-016-0667-y

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


  24 in total

1.  High-level reasoning and base-rate use: do we need cue-competition to explain the inverse base-rate effect?

Authors:  P Juslin; P Wennerholm; A Winman
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2001-05       Impact factor: 3.051

2.  Can attentional theory explain the inverse base rate effect? Comment on Kruschke (2001).

Authors:  Anders Winman; Pia Wennerholm; Peter Juslin
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2003-11       Impact factor: 3.051

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Authors:  Hilary J Don; Evan J Livesey
Journal:  Q J Exp Psychol (Hove)       Date:  2015-01-08       Impact factor: 2.143

5.  Rule abstraction, model-based choice, and cognitive reflection.

Authors:  Hilary J Don; Micah B Goldwater; A Ross Otto; Evan J Livesey
Journal:  Psychon Bull Rev       Date:  2016-10

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Authors:  D L Medin; S M Edelson
Journal:  J Exp Psychol Gen       Date:  1988-03

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Authors:  J K Kruschke
Journal:  J Exp Psychol Learn Mem Cogn       Date:  1996-01       Impact factor: 3.051

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Authors:  Danielle M Karazinov; Robert A Boakes
Journal:  Q J Exp Psychol B       Date:  2004-04

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Authors:  Danielle M Karazinov; Robert A Boakes
Journal:  Q J Exp Psychol (Hove)       Date:  2007-03       Impact factor: 2.143

10.  Attention, predictive learning, and the inverse base-rate effect: evidence from event-related potentials.

Authors:  Andy J Wills; Aureliu Lavric; Yvonne Hemmings; Ed Surrey
Journal:  Neuroimage       Date:  2013-11-02       Impact factor: 6.556

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  2 in total

1.  Dissecting EXIT.

Authors:  Samuel Paskewitz; Matt Jones
Journal:  J Math Psychol       Date:  2020-05-12       Impact factor: 1.387

2.  Causal illusions in the classroom: how the distribution of student outcomes can promote false instructional beliefs.

Authors:  Kit S Double; Julie Y L Chow; Evan J Livesey; Therese N Hopfenbeck
Journal:  Cogn Res Princ Implic       Date:  2020-08-03
  2 in total

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