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

How 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...

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Vydáno v:	Consciousness and cognition Ročník 21; číslo 1; s. 422 - 430
Hlavní autoři:	Maniscalco, Brian, Lau, Hakwan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier 01.03.2012 Elsevier BV
Témata:	Biological and medical sciences Cognition Cognition & reasoning Cognition. Intelligence Confidence Fundamental and applied biological sciences. Psychology Humans Judgment Metacognition Miscellaneous Psychological Theory Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Self image Sensitivity and Specificity Signal Detection, Psychological Signal-To-Noise Ratio Space Perception Human Signal detection theory Sensitivity Confidence rating Confidence Metacognition Type 2 sensitivity Cognition Measurement method Psychophysics Signal detection
ISSN:	1053-8100, 1090-2376, 1090-2376
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Shrnutí:	How 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.
Bibliografie:	ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Undefined-1 ObjectType-Feature-3 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	1053-8100 1090-2376 1090-2376
DOI:	10.1016/j.concog.2011.09.021