2022
DOI: 10.1249/jes.0000000000000308
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Rethinking the Statistical Analysis of Neuromechanical Data

Abstract: Mixed-effects models will improve data representation, promote superior experimental designs, and increase the validity and reproducibility of research findings.

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Cited by 20 publications
(13 citation statements)
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“…We assessed all outcomes of the 200 m trials at self-perceived 800 m race pace and spatiotemporal variables at long distance pace with a linear-mixed effect model (LMEM). 37 The LMEM had spike condition and sex as fixed effects, participant as a random intercept and speed and spatiotemporal variables as the output variables. Additionally, we used LMEM for all outcome variables of the 3,000 m time trials (speed, stride frequency and contact time) and RE trials with spike condition as fixed effects and participant as a random intercept.…”
Section: Discussionmentioning
confidence: 99%
“…We assessed all outcomes of the 200 m trials at self-perceived 800 m race pace and spatiotemporal variables at long distance pace with a linear-mixed effect model (LMEM). 37 The LMEM had spike condition and sex as fixed effects, participant as a random intercept and speed and spatiotemporal variables as the output variables. Additionally, we used LMEM for all outcome variables of the 3,000 m time trials (speed, stride frequency and contact time) and RE trials with spike condition as fixed effects and participant as a random intercept.…”
Section: Discussionmentioning
confidence: 99%
“…Finally, many of the prior studies pooled the identified MU discharges, violating the principle of co-dependence of observations (Tenan et al ., 2014). Conversely, we used linear mixed statistical modelling, accounting for nesting of observations within individual participant (Yu et al ., 2022; Wilkinson et al ., 2023). Finally, in most of the studies showing a progressive decrease in MU discharge rate to task failure, an intrinsic hand muscle was used (Carpentier et al ., 2001; McManus et al ., 2016).…”
Section: Discussionmentioning
confidence: 99%
“…Relations between correlation values of motor units, modes and each protocol were measured using single‐factor (one‐way) ANOVA with Tukey post hoc corrections. We considered analysing the data with linear mixed‐effects models, which offers a method for clustering replicate data by intervention and participant (Wilkinson et al, 2023). However, we opted for ANOVAs to accommodate different sample sizes for each participant and intervention, as well as the fact that motor units were not explicitly tracked across tasks.…”
Section: Methodsmentioning
confidence: 99%