Using theoretical constraints and the TASI taxonomy to delineate predictably replicable findings

• Verfasst von: Fiedler, Klaus [VerfasserIn]
• Verfasst von: Trafimow, David [VerfasserIn]
• Titel: Using theoretical constraints and the TASI taxonomy to delineate predictably replicable findings
• Verf.angabe: Klaus Fiedler, David Trafimow
• E-Jahr: 2024
• Jahr: 27 June 2024
• Umfang: 18 S.
• Fussnoten: Gesehen am 29.01.2025
• Titel Quelle: Enthalten in: Psychonomic bulletin & review
• Ort Quelle: New York, NY : Springer, 1994
• Jahr Quelle: 2024
• Band/Heft Quelle: 31(2024), 6, Seite 2581-2598
• ISSN Quelle: 1531-5320
• DOI: doi:10.3758/s13423-024-02521-4
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: A priori constraints
• Sach-SW: Auxiliary assumptions
• Sach-SW: Empirical laws
• Sach-SW: Inferential assumptions
• Sach-SW: Modelling constraints
• Sach-SW: Psychophysical constraints
• Sach-SW: Statistical assumptions
• K10plus-PPN: 1915872219

Abstract

The focus of the present article is not on failures to replicate but on the more optimistically framed and more fruitful question: What stable findings can be reproduced reliably and can be trusted by decision makers, managers, health agents, or politicians? We propagate the working hypothesis that a twofold key to stable and replicable findings lies in the existence of theoretical constraints and, no less important, in researchers’ sensitivity to metatheoretical, auxiliary assumptions. We introduce a hierarchy of four levels of theoretical constraints—a priori principles, psychophysical, empirical, and modelling constraints—combined with the TASI taxonomy of theoretical, auxiliary, statistical, and inferential assumptions Trafimow, Journal for the Theory of Social Behaviour, 52, 37-48, (2022). Although theoretical constraints clearly facilitate stable and replicable research findings, TASI reminds us of various reasons why even perfectly valid hypotheses need not always be borne out. The presented framework should help researchers to operationalize conditions under which theoretical constraints render empirical findings most predictable.