Literature DB >> 16608757

Participant recruitment methods and statistical reasoning performance.

Gary L Brase1, Laurence Fiddick, Clare Harries.   

Abstract

Optimal Bayesian reasoning performance has reportedly been elusive, and a variety of explanations have been suggested for this situation. In a series of experiments, it is demonstrated that these difficulties with replication can be accounted for by differences in participant-sampling methodologies. Specifically, the best performances are obtained with students from top-tier, national universities who were paid for their participation. Performance drops significantly as these conditions are altered regarding inducements (e.g., using unpaid participants) or participant source (e.g., using participants from a second-tier, regional university). Honours-programme undergraduates do better than regular undergraduates within the same university, paid participation creates superior performance, and top-tier university students do better than students from lower ranked universities. Pictorial representations (supplementing problem text) usually have a slight facilitative effect across these participant manipulations. These results indicate that studies should take account of these methodological details and focus more on relative levels of performance rather than absolute performance.

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Mesh:

Year:  2006        PMID: 16608757     DOI: 10.1080/02724980543000132

Source DB:  PubMed          Journal:  Q J Exp Psychol (Hove)        ISSN: 1747-0218            Impact factor:   2.143


  9 in total

1.  Frequency interpretation of ambiguous statistical information facilitates Bayesian reasoning.

Authors:  Gary L Brase
Journal:  Psychon Bull Rev       Date:  2008-04

2.  Whose statistical reasoning is facilitated by a causal structure intervention?

Authors:  Simon McNair; Aidan Feeney
Journal:  Psychon Bull Rev       Date:  2015-02

Review 3.  Reasoning and choice in the Monty Hall Dilemma (MHD): implications for improving Bayesian reasoning.

Authors:  Elisabet Tubau; David Aguilar-Lleyda; Eric D Johnson
Journal:  Front Psychol       Date:  2015-03-31

Review 4.  Good fences make for good neighbors but bad science: a review of what improves Bayesian reasoning and why.

Authors:  Gary L Brase; W Trey Hill
Journal:  Front Psychol       Date:  2015-03-31

5.  Beyond the status-quo: research on Bayesian reasoning must develop in both theory and method.

Authors:  Simon J McNair
Journal:  Front Psychol       Date:  2015-02-06

6.  Do Different Mental Models Influence Cybersecurity Behavior? Evaluations via Statistical Reasoning Performance.

Authors:  Gary L Brase; Eugene Y Vasserman; William Hsu
Journal:  Front Psychol       Date:  2017-11-02

7.  Interindividual differences in incentive sensitivity moderate motivational effects of competition and cooperation on motor performance.

Authors:  Florian Müller; Rouwen Cañal-Bruland
Journal:  PLoS One       Date:  2020-09-18       Impact factor: 3.240

8.  Tversky and Kahneman's Cognitive Illusions: Who Can Solve Them, and Why?

Authors:  Georg Bruckmaier; Stefan Krauss; Karin Binder; Sven Hilbert; Martin Brunner
Journal:  Front Psychol       Date:  2021-04-12

Review 9.  Comprehension and computation in Bayesian problem solving.

Authors:  Eric D Johnson; Elisabet Tubau
Journal:  Front Psychol       Date:  2015-07-27
  9 in total

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