Chemnitz University of Technology, Thüringer Weg 11, 09126 Chemnitz, Germany.
Chemnitz University of Technology, Thüringer Weg 11, 09126 Chemnitz, Germany.
J Biomech. 2023 Mar;149:111506. doi: 10.1016/j.jbiomech.2023.111506. Epub 2023 Feb 15.
Most biomechanical processes are continuous in nature. Measurement systems record this continuous behavior as curve data, which is often treated inappropriately in validation studies. The current paper compares different statistical models for analyzing the agreement of curves from two measurement systems. All models were evaluated in various error scenarios (simulated and real-world data). Excellent results were obtained using a functional method, with coverage probabilities close to the desired level in all data sets. Pointwise constructed bands had a lower coverage probability, but still contained most of the curve points and may thus be an option in scenarios where assumptions of functional models are violated (e.g., when curves are much noisier than those presented here, or in the presence of drift). Models that account for within-subject variation showed a higher coverage probability and less uncertainty about the variation of band limits. We hope this study, along with the provided research code, will inspire researchers to use methods for curve data more frequently and appropriately.
大多数生物力学过程本质上是连续的。测量系统将这种连续行为记录为曲线数据，而在验证研究中，这些曲线数据通常处理不当。本文比较了不同的统计模型，用于分析来自两种测量系统的曲线的一致性。所有模型都在各种误差情况下（模拟和真实数据）进行了评估。使用功能方法可以获得极好的结果，在所有数据集的置信区间概率都接近预期水平。逐点构建的带宽置信区间的概率较低，但仍包含了大部分曲线点，因此在违反功能模型假设的情况下（例如，当曲线比这里呈现的曲线噪声大得多，或者存在漂移时），可能是一种选择。考虑到个体内变异的模型显示出更高的置信区间概率和对带宽变异的不确定性更小。我们希望这项研究以及提供的研究代码能够激励研究人员更频繁地、更恰当地使用曲线数据方法。
