Literature DB >> 29048176

Meta-analysis of the effect of natural frequencies on Bayesian reasoning.

Michelle McDowell1, Perke Jacobs2.   

Abstract

The natural frequency facilitation effect describes the finding that people are better able to solve descriptive Bayesian inference tasks when represented as joint frequencies obtained through natural sampling, known as natural frequencies, than as conditional probabilities. The present meta-analysis reviews 20 years of research seeking to address when, why, and for whom natural frequency formats are most effective. We review contributions from research associated with the 2 dominant theoretical perspectives, the ecological rationality framework and nested-sets theory, and test potential moderators of the effect. A systematic review of relevant literature yielded 35 articles representing 226 performance estimates. These estimates were statistically integrated using a bivariate mixed-effects model that yields summary estimates of average performances across the 2 formats and estimates of the effects of different study characteristics on performance. These study characteristics range from moderators representing individual characteristics (e.g., numeracy, expertise), to methodological differences (e.g., use of incentives, scoring criteria) and features of problem representation (e.g., short menu format, visual aid). Short menu formats (less computationally complex representations showing joint-events) and visual aids demonstrated some of the strongest moderation effects, improving performance for both conditional probability and natural frequency formats. A number of methodological factors (e.g., exposure to both problem formats) were also found to affect performance rates, emphasizing the importance of a systematic approach. We suggest how research on Bayesian reasoning can be strengthened by broadening the definition of successful Bayesian reasoning to incorporate choice and process and by applying different research methodologies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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Year:  2017        PMID: 29048176     DOI: 10.1037/bul0000126

Source DB:  PubMed          Journal:  Psychol Bull        ISSN: 0033-2909            Impact factor:   17.737


  18 in total

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Authors:  Elisabet Tubau; Javier Rodríguez-Ferreiro; Itxaso Barberia; Àngels Colomé
Journal:  Psychol Res       Date:  2018-06-21

2.  Which cognitive individual differences predict good Bayesian reasoning? Concurrent comparisons of underlying abilities.

Authors:  Gary Brase
Journal:  Mem Cognit       Date:  2021-02

3.  What facilitates Bayesian reasoning? A crucial test of ecological rationality versus nested sets hypotheses.

Authors:  Gary Brase
Journal:  Psychon Bull Rev       Date:  2021-04

Review 4.  Perspectives on the 2 × 2 Matrix: Solving Semantically Distinct Problems Based on a Shared Structure of Binary Contingencies.

Authors:  Hansjörg Neth; Nico Gradwohl; Dirk Streeb; Daniel A Keim; Wolfgang Gaissmaier
Journal:  Front Psychol       Date:  2021-02-09

5.  Experiencing statistical information improves children's and adults' inferences.

Authors:  Christin Schulze; Ralph Hertwig
Journal:  Psychon Bull Rev       Date:  2022-06-01

Review 6.  Synergy between research on ensemble perception, data visualization, and statistics education: A tutorial review.

Authors:  Lucy Cui; Zili Liu
Journal:  Atten Percept Psychophys       Date:  2021-01-03       Impact factor: 2.199

7.  Processing Probability Information in Nonnumerical Settings - Teachers' Bayesian and Non-bayesian Strategies During Diagnostic Judgment.

Authors:  Timo Leuders; Katharina Loibl
Journal:  Front Psychol       Date:  2020-07-03

8.  The Effects of Working Memory and Probability Format on Bayesian Reasoning.

Authors:  Lin Yin; Zifu Shi; Zixiang Liao; Ting Tang; Yuntian Xie; Shun Peng
Journal:  Front Psychol       Date:  2020-05-12

9.  Visualizing the Bayesian 2-test case: The effect of tree diagrams on medical decision making.

Authors:  Karin Binder; Stefan Krauss; Georg Bruckmaier; Jörg Marienhagen
Journal:  PLoS One       Date:  2018-03-27       Impact factor: 3.240

10.  Why Can Only 24% Solve Bayesian Reasoning Problems in Natural Frequencies: Frequency Phobia in Spite of Probability Blindness.

Authors:  Patrick Weber; Karin Binder; Stefan Krauss
Journal:  Front Psychol       Date:  2018-10-12
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