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Article: A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings

TitleA signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings
Authors
KeywordsConfidence rating
Type 2 sensitivity
Signal detection theory
Metacognition
Issue Date2012
Citation
Consciousness and Cognition, 2012, v. 21, n. 1, p. 422-430 How to Cite?
AbstractHow should we measure metacognitive (" type 2" ) sensitivity, i.e. the efficacy with which observers' confidence ratings discriminate between their own correct and incorrect stimulus classifications? We argue that currently available methods are inadequate because they are influenced by factors such as response bias and type 1 sensitivity (i.e. ability to distinguish stimuli). Extending the signal detection theory (SDT) approach of . Galvin, Podd, Drga, and Whitmore (2003), we propose a method of measuring type 2 sensitivity that is free from these confounds. We call our measure meta- d', which reflects how much information, in signal-to-noise units, is available for metacognition. Applying this novel method in a 2-interval forced choice visual task, we found that subjects' metacognitive sensitivity was close to, but significantly below, optimality. We discuss the theoretical implications of these findings, as well as related computational issues of the method. We also provide free Matlab code for implementing the analysis. © 2011 Elsevier Inc.
Persistent Identifierhttp://hdl.handle.net/10722/242623
ISSN
2023 Impact Factor: 2.1
2023 SCImago Journal Rankings: 0.827
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorManiscalco, Brian-
dc.contributor.authorLau, Hakwan-
dc.date.accessioned2017-08-10T10:51:09Z-
dc.date.available2017-08-10T10:51:09Z-
dc.date.issued2012-
dc.identifier.citationConsciousness and Cognition, 2012, v. 21, n. 1, p. 422-430-
dc.identifier.issn1053-8100-
dc.identifier.urihttp://hdl.handle.net/10722/242623-
dc.description.abstractHow should we measure metacognitive (" type 2" ) sensitivity, i.e. the efficacy with which observers' confidence ratings discriminate between their own correct and incorrect stimulus classifications? We argue that currently available methods are inadequate because they are influenced by factors such as response bias and type 1 sensitivity (i.e. ability to distinguish stimuli). Extending the signal detection theory (SDT) approach of . Galvin, Podd, Drga, and Whitmore (2003), we propose a method of measuring type 2 sensitivity that is free from these confounds. We call our measure meta- d', which reflects how much information, in signal-to-noise units, is available for metacognition. Applying this novel method in a 2-interval forced choice visual task, we found that subjects' metacognitive sensitivity was close to, but significantly below, optimality. We discuss the theoretical implications of these findings, as well as related computational issues of the method. We also provide free Matlab code for implementing the analysis. © 2011 Elsevier Inc.-
dc.languageeng-
dc.relation.ispartofConsciousness and Cognition-
dc.subjectConfidence rating-
dc.subjectType 2 sensitivity-
dc.subjectSignal detection theory-
dc.subjectMetacognition-
dc.titleA signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.concog.2011.09.021-
dc.identifier.pmid22071269-
dc.identifier.scopuseid_2-s2.0-84857504962-
dc.identifier.volume21-
dc.identifier.issue1-
dc.identifier.spage422-
dc.identifier.epage430-
dc.identifier.eissn1090-2376-
dc.identifier.isiWOS:000301761900041-
dc.identifier.issnl1053-8100-

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