Confidence interval estimation of the intraclass correlation coefficient for binary outcome data.
We obtain closed-form asymptotic variance formulae for three point estimators of the intraclass correlation coefficient that may be applied to binary outcome data arising in clusters of variable size. Our results include as special cases those that have previously appeared in the literature (Fleiss and Cuzick, 1979, Applied Psychological Measurement 3, 537-542; Bloch and Kraemer, 1989, Biometrics 45, 269-287; Altaye, Donner, and Klar, 2001, Biometrics 57, 584-588). Simulation results indicate that confidence intervals based on the estimator proposed by Fleiss and Cuzick provide coverage levels close to nominal over a wide range of parameter combinations. Two examples are presented.
Zou
Guangyong
G
Robarts Clinical Trials, Robarts Research Institute, London, Ontario N6A 5K8, Canada. gzou@robarts.ca
Donner
Allan
A
D001699:Biometry / Q000379:methods*; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D001523:Mental Disorders / Q000145:classification / Q000175:diagnosis; D015233:Models, Statistical; D009010:Monte Carlo Method; D029424:Pulmonary Disease, Chronic Obstructive / Q000209:etiology / Q000235:genetics