Kappa statistic for clustered dichotomous responses from physicians and patients |
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| Authors: | Chaeryon Kang Bahjat Qaqish Jane Monaco Stacey L. Sheridan Jianwen Cai |
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| Affiliation: | 1. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, , Seattle, WA 98109, U.S.A.;2. Department of Biostatistics, The University of North Carolina at Chapel Hill, , Chapel Hill, NC 27599, U.S.A.;3. Department of Medicine, Division of General Medicine and Clinical Epidemiology, University of North Carolina at Chapel Hill, , Chapel Hill, NC, 27599 U.S.A.;4. Center for Health Promotion and Disease Prevention, University of North Carolina, , Chapel Hill, NC, U.S.A. |
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| Abstract: | The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician–patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared with the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. We present an example of an application to a coronary heart disease prevention study. Copyright © 2013 John Wiley & Sons, Ltd. |
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| Keywords: | Cluster bootstrap resampling Clustered dichotomous responses Kappa statistic |
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