Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, United States of America.
Physiol Meas. 2020 Jun 15;41(5):055012. doi: 10.1088/1361-6579/ab86d6.
The rapid emergence of new measurement instruments and methods requires personnel and researchers of different disciplines to know the correct statistical methods to utilize to compare their performance with reference ones and properly interpret findings. We discuss the often-made mistake of applying the inappropriate correlation and regression statistical approaches to compare methods and then explain the concepts of agreement and reliability. Then, we introduce the intraclass correlation as a measure of inter-rater reliability, and the Bland-Altman plot as a measure of agreement, and we provide formulae to calculate them along with illustrative examples for different types of study designs, specifically single measurement per subject, repeated measurement while the true value is constant, and repeated measurement when the true value is not constant. We emphasize the requirement to validate the assumptions of these statistical approaches, and also how to deal with violations and provide formulae on how to calculate the confidence interval for estimated values of agreement and intraclass correlation. Finally, we explain how to interpret and report the findings of these statistical analyses.
新的测量仪器和方法的迅速出现,要求不同学科的人员和研究人员了解正确的统计方法,以便将其性能与参考方法进行比较,并正确解释研究结果。我们讨论了经常犯的一个错误,即不恰当地应用相关和回归统计方法来比较方法,然后解释了一致性和可靠性的概念。然后,我们介绍了组内相关作为一种评价者间可靠性的指标,以及 Bland-Altman 图作为一种一致性的评价指标,并提供了用于不同类型研究设计的计算公式,特别是针对每个受试者的单次测量、当真实值不变时的重复测量以及当真实值变化时的重复测量。我们强调了需要验证这些统计方法的假设,以及如何处理违反假设的情况,并提供了有关如何计算一致性和组内相关估计值的置信区间的公式。最后,我们解释了如何解释和报告这些统计分析的结果。