Department of Physics, Stockholm University, Stockholm, Sweden.
Department of Neurobiology, Care Science and Society, Division of Physiotherapy, Karolinska Institutet, Stockholm, Sweden.
PLoS One. 2019 Jul 22;14(7):e0219854. doi: 10.1371/journal.pone.0219854. eCollection 2019.
A re-analysis of intraclass correlation (ICC) theory is presented together with Monte Carlo simulations of ICC probability distributions. A partly revised and simplified theory of the single-score ICC is obtained, together with an alternative and simple recipe for its use in reliability studies. Our main, practical conclusion is that in the analysis of a reliability study it is neither necessary nor convenient to start from an initial choice of a specified statistical model. Rather, one may impartially use all three single-score ICC formulas. A near equality of the three ICC values indicates the absence of bias (systematic error), in which case the classical (one-way random) ICC may be used. A consistency ICC larger than absolute agreement ICC indicates the presence of non-negligible bias; if so, classical ICC is invalid and misleading. An F-test may be used to confirm whether biases are present. From the resulting model (without or with bias) variances and confidence intervals may then be calculated. In presence of bias, both absolute agreement ICC and consistency ICC should be reported, since they give different and complementary information about the reliability of the method. A clinical example with data from the literature is given.
本文重新分析了组内相关系数(ICC)理论,并通过蒙特卡罗模拟对 ICC 概率分布进行了模拟。得到了单指标 ICC 的部分修订和简化理论,以及一种替代的、简单的 ICC 在可靠性研究中使用的方法。我们的主要实用结论是,在可靠性研究的分析中,从指定统计模型的初始选择开始既没有必要也不方便。相反,人们可以公正地使用所有三个单指标 ICC 公式。如果三个 ICC 值非常接近,则表明不存在偏差(系统误差),此时可以使用经典的(单向随机)ICC。一致性 ICC 大于绝对一致性 ICC 表明存在不可忽略的偏差;如果是这样,经典 ICC 是无效和误导的。可以使用 F 检验来确认是否存在偏差。然后,可以根据得出的模型(有或没有偏差)计算方差和置信区间。如果存在偏差,则应报告绝对一致性 ICC 和一致性 ICC,因为它们提供了关于方法可靠性的不同且互补的信息。本文提供了一个临床实例,数据来自文献。