Rethinking the Statistical Analysis of Neuromechanical Data.
| Autor: | Wilkinson RD; Department of Integrative Physiology, University of Colorado, Boulder, CO., Mazzo MR; Strive Health, Denver, CO., Feeney DF; Performance Fit Laboratory, BOA Technology Inc., Denver, CO. |
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| Jazyk: | angličtina |
| Zdroj: | Exercise and sport sciences reviews [Exerc Sport Sci Rev] 2023 Jan 01; Vol. 51 (1), pp. 43-50. Date of Electronic Publication: 2022 Oct 10. |
| DOI: | 10.1249/JES.0000000000000308 |
| Abstrakt: | Researchers in neuromechanics should upgrade their statistical toolbox. We propose linear mixed-effects models in place of commonly used statistical tests to better capture subject-specific baselines and treatment-associated effects that naturally occur in neuromechanics. Researchers can use this approach to handle sporadic missing data, avoid the assumption of conditional independence in observations, and successfully model complex experimental protocols. (Copyright © 2022 by the American College of Sports Medicine.) |
| Databáze: | MEDLINE |
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