title: Kappa statistic for clustered dichotomous responses from physicians and patients.
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.
authors.affiliation: Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
authors.forename: Chaeryon
authors.initials: C
authors.lastname: Kang
authors.forename: Bahjat
authors.initials: B
authors.lastname: Qaqish
authors.forename: Jane
authors.initials: J
authors.lastname: Monaco
authors.forename: Stacey L
authors.initials: SL
authors.lastname: Sheridan
authors.forename: Jianwen
authors.initials: J
authors.lastname: Cai
mesh_terms: D016000:Cluster Analysis; D003198:Computer Simulation; D003327:Coronary Disease; D006801:Humans; D015588:Observer Variation; D010353:Patient Education as Topic; D010361:Patients; D010820:Physicians; D013223:Statistics as Topic / Q000592:standards*
keywords: Cluster bootstrap resampling; Clustered dichotomous responses; Kappa statistic