TY - JOUR
T1 - Robust estimators of the concordance correlation coefficient
AU - King, T. S.
AU - Chinchilli, V. M.
N1 - Funding Information:
This research was partially supported by National Institute of Environmental Health Sciences Training Grant #5-T32-ES07018. The authors thank Professor Ge-rardo Heiss at the Collaborative Studies Coordinating Center at the University of North Carolina in Chapel Hill, NC, for use of example data from the ARIC study.
PY - 2001
Y1 - 2001
N2 - This paper proposes a generalized version of Lin's (1989, Biometrics 45, 255-268) concordance correlation coefficient for the agreement assessment of continuous data. Lin's coefficient evaluates the accuracy and precision between two measures, and is based on the expected value of the squared distance function. We generalize Lin's coefficient, apply alternative distance functions, and produce more robust versions of the concordance correlation coefficient. In this paper, we develop the asymptotic theory for this class of estimators, investigate small-sample properties via computer simulation, and demonstrate their use with two real data examples.
AB - This paper proposes a generalized version of Lin's (1989, Biometrics 45, 255-268) concordance correlation coefficient for the agreement assessment of continuous data. Lin's coefficient evaluates the accuracy and precision between two measures, and is based on the expected value of the squared distance function. We generalize Lin's coefficient, apply alternative distance functions, and produce more robust versions of the concordance correlation coefficient. In this paper, we develop the asymptotic theory for this class of estimators, investigate small-sample properties via computer simulation, and demonstrate their use with two real data examples.
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U2 - 10.1081/BIP-100107651
DO - 10.1081/BIP-100107651
M3 - Article
C2 - 11725932
AN - SCOPUS:0035156749
SN - 1054-3406
VL - 11
SP - 83
EP - 105
JO - Journal of Biopharmaceutical Statistics
JF - Journal of Biopharmaceutical Statistics
IS - 3
ER -