Estimating the Generalized Concordance Correlation Coefficient through Variance Components
Article first published online: 11 DEC 2003
Volume 59, Issue 4, pages 849–858, December 2003
How to Cite
Carrasco, J. L. and Jover, L. (2003), Estimating the Generalized Concordance Correlation Coefficient through Variance Components. Biometrics, 59: 849–858. doi: 10.1111/j.0006-341X.2003.00099.x
- Issue published online: 11 DEC 2003
- Article first published online: 11 DEC 2003
- Received November 2002. Revised April 2003. Accepted April 2003.
- Concordance correlation coefficient;
- Intraclass correlation coefficient;
- Mixed effects model;
- Variance components
Summary. 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.