title: Testing the equality of two dependent kappa statistics.
abstract: Procedures are developed and compared for testing the equality of two dependent kappa statistics in the case of two raters and a dichotomous outcome variable. Such problems may arise when each of a sample of subjects are rated under two distinct settings, and it is of interest to compare the observed levels of inter-observer and intra-observer agreement. The procedures compared are extensions of previously developed procedures for comparing kappa statistics computed from independent samples. The results of a Monte Carlo simulation show that adjusting for the dependency between samples tends to be worthwhile only if the between-setting correlation is comparable in magnitude to the within-setting correlations. In this case, a goodness-of-fit procedure that takes into account the dependency between samples is recommended.
authors.affiliation: Department of Epidemiology and Biostatistics, The University of Western Ontario, London, Ontario, N6A 5C1, Canada.
authors.forename: A
authors.initials: A
authors.lastname: Donner
authors.forename: M M
authors.initials: MM
authors.lastname: Shoukri
authors.forename: N
authors.initials: N
authors.lastname: Klar
authors.forename: E
authors.initials: E
authors.lastname: Bartfay
mesh_terms: D000704:Analysis of Variance; D001699:Biometry / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D015588:Observer Variation