School of Kinesiology, Louisiana State University, United States.
Institute of Public and Preventive Health, Augusta University, United States.
J Sci Med Sport. 2021 Jan;24(1):67-73. doi: 10.1016/j.jsams.2020.08.009. Epub 2020 Sep 5.
This study investigated the structure of the Test of Gross Motor Development - 3rd edition (TGMD-3). Specifically, we examine bifactor structure, which simultaneously models a fundamental motor skills (FMS) general factor and specific factors for locomotor skills and ball skills, compared to other models.
Cross-sectional design using the TGMD-3 normative sample.
The sample (N = 862) of children (Mage = 6.51, SD = 2.23) was matched based on United States census data, ensuring appropriate percentages of demographic representation and disability status. Confirmatory factor analyses, exploratory structural equation modeling, model-based reliability estimates including coefficient omega hierarchical, and coefficient omega hierarchical subscale, explained common variance estimates, and relative parameter bias were examined.
Findings revealed bifactor structure produced a better model fit compared to both one-factor and two-factor models. Furthermore, model reliability estimates that parceled true score variance for the general FMS factor, locomotor skills factor, and ball skills factor yielded high internal consistency for FMS (.797) but not locomotor skills (.168) and ball skills (.216). Finally, explained common variance (.852-.879) and relative parameter bias (.018-.072) estimates identified the strength of the run, skip, slide, and dribble skills tests to represent the FMS general factor.
Our findings demonstrate the advantages of using bifactor structure to examine the TGMD-3 compared to one-factor and two-factor models. Additionally, these results provide further evidence that using the TGMD-3 to examine an overall FMS general factor may explain more variance in performance and provide a better picture for evaluating children's current FMS levels compared to subscales independently.
本研究探讨了《运动发育测试-第三版》(TGMD-3)的结构。具体而言,我们考察了双因素结构,该结构同时对基本运动技能(FMS)总因素以及运动技能和球技的特定因素进行建模,与其他模型相比。
使用 TGMD-3 规范样本的横断面设计。
根据美国人口普查数据,对儿童样本(Mage=6.51,SD=2.23)进行匹配,以确保适当的人口统计代表比例和残疾状况。对确认性因子分析、探索性结构方程建模、基于模型的可靠性估计,包括系数 omega 层次和系数 omega 层次子量表、解释共同方差估计以及相对参数偏差进行了检验。
研究结果表明,与单因素和双因素模型相比,双因素结构产生了更好的模型拟合度。此外,将 FMS 总因素、运动技能因素和球技因素的真实分数方差划分的模型可靠性估计,为 FMS(.797)提供了高的内部一致性,但为运动技能(.168)和球技(.216)则没有。最后,解释共同方差(.852-.879)和相对参数偏差(.018-.072)估计确定了跑、跳、滑和运球技能测试代表 FMS 总因素的强度。
我们的研究结果表明,与单因素和双因素模型相比,使用双因素结构来检查 TGMD-3 具有优势。此外,这些结果进一步证明,使用 TGMD-3 来检查总体 FMS 总因素可以解释更多的表现差异,并与子量表独立相比,提供更好的儿童当前 FMS 水平评估。