Predicted as observed? How to identify empirically adequate theoretical constructs
The identification of an empirically adequate theoretical construct requires determining whether a theoretically predicted effect is sufficiently similar to an observed effect. To this end, we propose a simple similarity measure, describe its application in different research designs, and use comput...
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Published in | Frontiers in psychology Vol. 13; p. 980261 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
01.12.2022
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Subjects | |
Online Access | Get full text |
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Summary: | The identification of an empirically adequate theoretical construct requires determining whether a theoretically predicted effect is sufficiently similar to an observed effect. To this end, we propose a simple similarity measure, describe its application in different research designs, and use computer simulations to estimate the necessary sample size for a given observed effect. As our main example, we apply this measure to recent meta-analytical research on precognition. Results suggest that the evidential basis is too weak for a predicted precognition effect of
= 0.20 to be considered empirically adequate. As additional examples, we apply this measure to object-level experimental data from dissonance theory and a recent crowdsourcing hypothesis test, as well as to meta-analytical data on the correlation of personality traits and life outcomes. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 This article was submitted to Theoretical and Philosophical Psychology, a section of the journal Frontiers in Psychology Reviewed by: Jan Ketil Arnulf, BI Norwegian Business School, Norway; Jean-Marie C. Chevalier, Université Paris-Est Créteil Val de Marne, France Frank Zenker https://orcid.org/0000-0001-7173-7964 ORCID: Erich H. Witte https://orcid.org/0000-0002-9446-3211 Adrian Stanciu https://orcid.org/0000-0001-8149-7829 Edited by: Luca Tummolini, National Research Council, Italy |
ISSN: | 1664-1078 1664-1078 |
DOI: | 10.3389/fpsyg.2022.980261 |