Murayama, K., Sakaki, M. ORCID: https://orcid.org/0000-0003-1993-5765, Yan, V. X. and Smith, G.
(2014)
Type-1 error inflation in the traditional by-participant analysis to metamemory accuracy: a generalized mixed-effects model perspective.
Journal of Experimental Psychology: Learning, Memory & Cognition, 40 (5).
pp. 1287-1306.
ISSN 0278-7393
doi: 10.1037/a0036914
Abstract/Summary
In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are entered into group-level statistical tests such as the t-test. In the current work, we argue that the by-participant analysis, regardless of the accuracy measurements used, would produce a substantial inflation of Type-1 error rates, when a random item effect is present. A mixed-effects model is proposed as a way to effectively address the issue, and our simulation studies examining Type-1 error rates indeed showed superior performance of mixed-effects model analysis as compared to the conventional by-participant analysis. We also present real data applications to illustrate further strengths of mixed-effects model analysis. Our findings imply that caution is needed when using the by-participant analysis, and recommend the mixed-effects model analysis.
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Item Type | Article |
URI | https://reading-clone.eprints-hosting.org/id/eprint/36409 |
Item Type | Article |
Refereed | Yes |
Divisions | Science Life Sciences > School of Psychology and Clinical Language Sciences > Department of Psychology Life Sciences > School of Psychology and Clinical Language Sciences > Language and Cognition |
Publisher | American Psychological Association. |
Publisher Statement | This article may not exactly replicate the final version published in the APA journal. It is not the copy of record |
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