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Biostatistics 1:191-202 (2000)
© 2000 Oxford University Press

Modeling kappa for measuring dependent categorical agreement data

John M. Williamson1, Stuart R. Lipsitz3 and Amita K. Manatunga2

1 Division of HIV/AIDS Prevention—Surveillance and Epidemiology (MS E-48), National Centers for HIV, STD, and TB Prevention, Centers for Disease Control and Prevention, 1600 Clifton Rd., NE, Atlanta, GA 30333, USA jow5{at}cdc.gov
2 Department of Biostatistics, The Rollins School of Public Health of Emory University, 1518 Clifton Rd., NE, Atlanta, GA 30322, USA
3 Department of Biometry and Epidemiology, Medical University of South Carolina, 135 Rutledge Avenue, Suite 1148, PO Box 250551, Charleston, SC 29425, USA

A method for analysing dependent agreement data with categorical responses is proposed. A generalized estimating equation approach is developed with two sets of equations. The first set models the marginal distribution of categorical ratings, and the second set models the pairwise association of ratings with the kappa coefficient () as a metric. Covariates can be incorporated into both sets of equations. This approach is compared with a latent variable model that assumes an underlying multivariate normal distribution in which the intraclass correlation coefficient is used as a measure of association. Examples are from a cervical ectopy study and the National Heart, Lung, and Blood Institute Veteran Twin Study.

Keywords: Correlated data; Interrater agreement; Kappa coefficient; Ordered categorical data


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