Baayen Corine, Klugkist Irene, Mechsner Franz
Department of Methodology and Statistics, University of Utrecht, the Netherlands.
J Mot Behav. 2012;44(5):351-63. doi: 10.1080/00222895.2012.709549. Epub 2012 Sep 13.
Researchers studying the movements of the human body often encounter data measured in angles (e.g., angular displacements of joints). The evaluation of these circular data requires special statistical methods. The authors introduce a new test for the analysis of order-constrained hypotheses for circular data. Through this test, researchers can evaluate their expectations regarding the outcome of an experiment directly by representing their ideas in the form of a hypothesis containing inequality constraints. The resulting data analysis is generally more powerful than one using standard null hypothesis testing. Two examples of circular data from human movement science are presented to illustrate the use of the test. Results from a simulation study show that the test performs well.
研究人体运动的研究人员经常会遇到以角度测量的数据（例如关节的角位移）。对这些圆形数据的评估需要特殊的统计方法。作者引入了一种新的检验方法，用于分析圆形数据的有序约束假设。通过这种检验，研究人员可以通过将他们的想法以包含不等式约束的假设形式表示出来，直接评估他们对实验结果的预期。由此产生的数据分析通常比使用标准零假设检验的分析更有效。给出了两个来自人体运动科学的圆形数据示例，以说明该检验的用法。模拟研究结果表明该检验效果良好。
