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首页> 外文期刊>American Journal of Sports Science and Medicine >Use of Loglinear Models to Investigate the Patterns of Association among Fitness Test Performances
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Use of Loglinear Models to Investigate the Patterns of Association among Fitness Test Performances

机译：使用对数线性模型调查适应性测试表现之间的关联模式

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Background: Physical fitness tests are often administered as a battery, allowing for several different fitness scores. Furthermore, fitness scores are generally considered outcome variables, with no one test causing the performance of another. Therefore, using loglinear models to examine the relationship between fitness test performances is appropriate. Methods: This study used data from a campus-based fitness study of college students. Four physical fitness measures were used in the analysis. Cardiorespiratory fitness (CRF) was assessed by a multi-stage running test (VO2max, ml/kg/min). Lower-body power was assessed by a countermovement vertical jump (VJ) test (inches). Muscular endurance was assessed by a maximal push-up (PU) test (repetitions). Muscular strength was assessed by a 1RM bench press (BP) test. Participants were categorized into high or low fitness groups using each sex-specific fitness score median. Results: Results of the initial hierarchical loglinear models indicated no significant four-way or three-way interactions. A simplified loglinear model with all two-factor interactions provided adequate fit to the data. The odds of high BP performance were much greater with high PU (OR=3.2) and VJ (OR=2.3) performance. The odds of high CRF performance were also greater with high PU (OR=2.4) and VJ (OR=2.7) performance. Finally, odds of high PU performance were much greater with high VJ (OR=3.6) performance. CRF and BP were statistically independent. Conclusion: Results from this study indicate that the performance on a fitness test can be related to at least one other fitness test performance.
机译：背景：体能测试通常以电池的形式进行，因此可以进行几种不同的体能评分。此外，适合度评分通常被视为结果变量，没有一项测试会导致另一项测试的表现。因此，使用对数线性模型来检验适应性测试性能之间的关系是合适的。方法：本研究使用了基于校园的大学生健身研究的数据。分析中使用了四种身体健康指标。通过多阶段跑步测试（VO2max，ml / kg / min）评估心脏呼吸适应性（CRF）。下肢力量通过反向运动垂直跳跃（VJ）测试（英寸）进行评估。通过最大俯卧撑（PU）测试（重复）评估肌肉耐力。肌肉力量通过1RM卧推（BP）测试进行评估。使用每个特定性别的健身得分中位数，将参与者分为高健身组或低健身组。结果：初始分层对数线性模型的结果表明没有明显的四向或三向相互作用。具有所有两因素相互作用的简化对数线性模型提供了对数据的充分拟合。高PU（OR = 3.2）和VJ（OR = 2.3）性能下，高BP性能的几率要大得多。高PU（OR = 2.4）和VJ（OR = 2.7）的情况下，高CRF性能的几率也更大。最后，具有高VJ（OR = 3.6）性能时，具有高PU性能的几率要大得多。 CRF和BP在统计学上是独立的。结论：这项研究的结果表明，体能测试的表现可能与至少一项其他体能测试的表现有关。

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