On the psychometric evaluation of cognitive control tasks: An Investigation with the Dual Mechanisms of Cognitive Control (DMCC) battery.

Autor: Snijder JP; Department of Psychology, Heidelberg University, Heidelberg, Germany. jean-paul.snijder@uni-heidelberg.de., Tang R; Department of Psychology, Washington University in St. Louis, St. Louis, MO, USA., Bugg JM; Department of Psychology, Washington University in St. Louis, St. Louis, MO, USA., Conway ARA; Division of Behavioral & Organizational Sciences, Claremont Graduate University, Claremont, CA, USA., Braver TS; Department of Psychology, Washington University in St. Louis, St. Louis, MO, USA.
Jazyk: angličtina
Zdroj: Behavior research methods [Behav Res Methods] 2024 Mar; Vol. 56 (3), pp. 1604-1639. Date of Electronic Publication: 2023 Apr 11.
DOI: 10.3758/s13428-023-02111-7
Abstrakt: The domain of cognitive control has been a major focus of experimental, neuroscience, and individual differences research. Currently, however, no theory of cognitive control successfully unifies both experimental and individual differences findings. Some perspectives deny that there even exists a unified psychometric cognitive control construct to be measured at all. These shortcomings of the current literature may reflect the fact that current cognitive control paradigms are optimized for the detection of within-subject experimental effects rather than individual differences. In the current study, we examine the psychometric properties of the Dual Mechanisms of Cognitive Control (DMCC) task battery, which was designed in accordance with a theoretical framework that postulates common sources of within-subject and individual differences variation. We evaluated both internal consistency and test-retest reliability, and for the latter, utilized both classical test theory measures (i.e., split-half methods, intraclass correlation) and newer hierarchical Bayesian estimation of generative models. Although traditional psychometric measures suggested poor reliability, the hierarchical Bayesian models indicated a different pattern, with good to excellent test-retest reliability in almost all tasks and conditions examined. Moreover, within-task, between-condition correlations were generally increased when using the Bayesian model-derived estimates, and these higher correlations appeared to be directly linked to the higher reliability of the measures. In contrast, between-task correlations remained low regardless of theoretical manipulations or estimation approach. Together, these findings highlight the advantages of Bayesian estimation methods, while also pointing to the important role of reliability in the search for a unified theory of cognitive control.
(© 2023. The Author(s).)
Databáze: MEDLINE
Externí odkaz: