Testing the equality of two dependent kappa statistics | Zendy

Donner Allan | Zendy; Shoukri Mohamed M. | Zendy; Klar Neil | Zendy; Bartfay Emma | Zendy

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Testing the equality of two dependent kappa statistics

Author(s) -

Donner Allan,

Shoukri Mohamed M.,

Klar Neil,

Bartfay Emma

Publication year - 2000

Publication title -

statistics in medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.996

H-Index - 183

eISSN - 1097-0258

pISSN - 0277-6715

DOI - 10.1002/(sici)1097-0258(20000215)19:3<373::aid-sim337>3.0.co;2-y

Subject(s) - statistics , kappa , correlation , monte carlo method , mathematics , cohen's kappa , goodness of fit , dependency (uml) , sample size determination , variable (mathematics) , computer science , artificial intelligence , mathematical analysis , geometry

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. Copyright © 2000 John Wiley & Sons, Ltd.

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