title: Testing the homogeneity of kappa statistics.
abstract: Procedures are compared for testing the homogeneity of k > or = 2 independent kappa statistics in the case of two raters and a dichotomous outcome. One of the procedures is based on the estimated large sample variance derived under a model frequently adopted for inferences concerning interobserver agreement. The other is based on a goodness-of-fit approach to this model. The results of a Monte Carlo simulation show that the two approaches have similar properties if the number of subjects in each sample is large (> 100), and the prevalence of the underlying trait of interest is not extreme, while the goodness-of-fit approach is recommended for comparisons involving smaller numbers of subjects or in which the prevalence of the underlying trait is small (< 0.3).
authors.affiliation: Department of Epidemiology and Biostatistics, University of Western Ontario, London, Canada.
authors.forename: A
authors.initials: A
authors.lastname: Donner
authors.forename: M
authors.initials: M
authors.lastname: Eliasziw
authors.forename: N
authors.initials: N
authors.lastname: Klar
mesh_terms: D000704:Analysis of Variance; D001699:Biometry / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D012167:Retinal Perforations / Q000150:complications; D014821:Vitrectomy; D018630:Vitreoretinopathy, Proliferative / Q000150:complications / Q000473:pathology / Q000601:surgery