Griffith Sports Science, Griffith University, Gold Coast, QLD,Australia.
Queensland Academy of Sport, Nathan, QLD,Australia.
Int J Sports Physiol Perform. 2022 Jul 1;17(8):1289-1295. doi: 10.1123/ijspp.2021-0496. Print 2022 Aug 1.
Sport-science research consistently contains repeated measures and imbalanced data sets. This study calls for further adoption of mixed models when analyzing longitudinal sport-science data sets. Mixed models were used to understand whether the level of competition affected the intensity of women's rugby league match play.
A total of 472 observations were used to compare the mean speed of female rugby league athletes recorded during club-, state-, and international-level competition. As athletes featured in all 3 levels of competition and there were multiple matches within each competition (ie, repeated measures), the authors demonstrated that mixed models are the appropriate statistical approach for these data.
The authors determined that if a repeated-measures analysis of variance (ANOVA) were used for the statistical analysis in the present study, at least 48.7% of the data would have been omitted to meet ANOVA assumptions. Using a mixed model, the authors determined that mean speed recorded during Trans-Tasman Test matches was 73.4 m·min-1, while the mean speeds for National Rugby League Women and State of Origin matches were 77.6 and 81.6 m·min-1, respectively. Random effects of team, athlete, and match all accounted for variations in mean speed, which otherwise could have concealed the main effects of position and level of competition had less flexible ANOVAs been used.
These data clearly demonstrate the appropriateness of applying mixed models to typical data sets acquired in the professional sport setting. Mixed models should be more readily used within sport science, especially in observational, longitudinal data sets such as movement pattern analyses.
运动科学研究经常包含重复测量和不平衡数据集。本研究呼吁在分析纵向运动科学数据集时进一步采用混合模型。混合模型用于了解比赛水平是否影响女子橄榄球联盟比赛的强度。
总共使用了 472 个观测值来比较俱乐部、州和国际级别比赛中女性橄榄球联盟运动员的平均速度。由于运动员在所有 3 个比赛级别中都有出现，并且每个比赛中都有多个比赛（即重复测量），作者证明混合模型是这些数据的适当统计方法。
作者确定，如果在本研究的统计分析中使用重复测量方差分析（ANOVA），则至少会有 48.7%的数据被省略以满足 ANOVA 假设。使用混合模型，作者确定在跨塔斯曼测试比赛中记录的平均速度为 73.4 m·min-1，而全国橄榄球联盟女子比赛和州际起源比赛的平均速度分别为 77.6 和 81.6 m·min-1。团队、运动员和比赛的随机效应都解释了平均速度的变化，如果使用更不灵活的 ANOVA，则位置和比赛水平的主要影响可能会被掩盖。
这些数据清楚地表明，混合模型适用于在职业体育环境中获得的典型数据集。混合模型应该更广泛地应用于运动科学中，特别是在运动模式分析等观察性、纵向数据集。
