Simple moment-based inferences of generalized concordance correlation

John J. Chen, Guangxiang Zhang, Chen Ji and George F. Steinhardt

Journal of Applied Statistics, 2011, vol. 38, issue 9, pages 1867-1882

Abstract: We proposed two simple moment-based procedures, one with (GCCC1) and one without (GCCC2) normality assumptions, to generalize the inference of concordance correlation coefficient for the evaluation of agreement among multiple observers for measurements on a continuous scale. A modified Fisher's Z-transformation was adapted to further improve the inference. We compared the proposed methods with U-statistic-based inference approach. Simulation analysis showed desirable statistical properties of the simplified approach GCCC1, in terms of coverage probabilities and coverage balance, especially for small samples. GCCC2, which is distribution-free, behaved comparably with the U-statistic-based procedure, but had a more intuitive and explicit variance estimator. The utility of these approaches were illustrated using two clinical data examples.

Date: 2011
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