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Characterizing belief bias in syllogistic reasoning: A hierarchical Bayesian meta-analysis of ROC data

Trippas, D; Kellen, D; Singmann, H; Pennycook, G; Koehler, DJ; Fugelsang, JA; Dube, C; (2018) Characterizing belief bias in syllogistic reasoning: A hierarchical Bayesian meta-analysis of ROC data. Psychonomic Bulletin & Review , 25 (6) pp. 2141-2174. 10.3758/s13423-018-1460-7. Green open access

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Abstract

The belief-bias effect is one of the most-studied biases in reasoning. A recent study of the phenomenon using the signal detection theory (SDT) model called into question all theoretical accounts of belief bias by demonstrating that beliefbased differences in the ability to discriminate between valid and invalid syllogisms may be an artifact stemming from the use of inappropriate linear measurement models such as analysis of variance (Dube et al., Psychological Review, 117(3), 831–863, 2010). The discrepancy between Dube et al.’s, Psychological Review, 117(3), 831–863 (2010) results and the previous three decades of work, together with former’s methodological criticisms suggests the need to revisit earlier results, this time collecting confidence-rating responses. Using a hierarchical Bayesian meta-analysis, we reanalyzed a corpus of 22 confidence-rating studies (N = 993). The results indicated that extensive replications using confidence-rating data are unnecessary as the observed receiver operating characteristic functions are not systematically asymmetric. These results were subsequently corroborated by a novel experimental design based on SDT’s generalized area theorem. Although the metaanalysis confirms that believability does not influence discriminability unconditionally, it also confirmed previous results that factors such as individual differences mediate the effect. The main point is that data from previous and future studies can be safely analyzed using appropriate hierarchical methods that do not require confidence ratings. More generally, our results set a new standard for analyzing data and evaluating theories in reasoning. Important methodological and theoretical considerations for future work on belief bias and related domains are discussed.

Type: Article
Title: Characterizing belief bias in syllogistic reasoning: A hierarchical Bayesian meta-analysis of ROC data
Open access status: An open access version is available from UCL Discovery
DOI: 10.3758/s13423-018-1460-7
Publisher version: http://dx.doi.org/10.3758/s13423-018-1460-7
Language: English
Additional information: Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Keywords: Deductive reasoning, Syllogisms, Belief bias, Signal detection theory, Hierarchical Bayesian, Meta-analysis
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/10107864
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