Carrasco Josep L, Jover Lluís
Bioestadística, Departament de Salut Pública, Universitat de Barcelona, Facultat de Medicina, Casanova, 143 08036 Barcelona, Spain.
Biometrics. 2003 Dec;59(4):849-58. doi: 10.1111/j.0006-341x.2003.00099.x.
The intraclass correlation coefficient (ICC) and the concordance correlation coefficient (CCC) are two of the most popular measures of agreement for variables measured on a continuous scale. Here, we demonstrate that ICC and CCC are the same measure of agreement estimated in two ways: by the variance components procedure and by the moment method. We propose estimating the CCC using variance components of a mixed effects model, instead of the common method of moments. With the variance components approach, the CCC can easily be extended to more than two observers, and adjusted using confounding covariates, by incorporating them in the mixed model. A simulation study is carried out to compare the variance components approach with the moment method. The importance of adjusting by confounding covariates is illustrated with a case example.
组内相关系数（ICC）和一致性相关系数（CCC）是用于连续尺度测量变量的两种最常用的一致性度量方法。在此，我们证明ICC和CCC是通过两种方式估计的相同一致性度量：方差分量法和矩量法。我们建议使用混合效应模型的方差分量来估计CCC，而不是常用的矩量法。采用方差分量法，通过将其纳入混合模型，CCC可以轻松扩展到两个以上的观察者，并使用混杂协变量进行调整。进行了一项模拟研究，以比较方差分量法和矩量法。通过一个案例说明了使用混杂协变量进行调整的重要性。
