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Homogeneity Score Test for the Intraclass Version of the Kappa Statistics and Sample‐Size Determination in Multiple or Stratified Studies
Author(s) -
Nam Junmo
Publication year - 2003
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2003.00118.x
Subject(s) - statistics , homogeneity (statistics) , kappa , mathematics , estimator , intraclass correlation , cohen's kappa , sample size determination , score test , goodness of fit , statistical hypothesis testing , psychometrics , geometry
Summary . When the intraclass correlation coefficient or the equivalent version of the kappa agreement coefficient have been estimated from several independent studies or from a stratified study, we have the problem of comparing the kappa statistics and combining the information regarding the kappa statistics in a common kappa when the assumption of homogeneity of kappa coefficients holds. In this article, using the likelihood score theory extended to nuisance parameters (Tarone, 1988, Communications in Statistics—Theory and Methods 17 (5), 1549–1556) we present an efficient homogeneity test for comparing several independent kappa statistics and, also, give a modified homogeneity score method using a noniterative and consistent estimator as an alternative. We provide the sample size using the modified homogeneity score method and compare it with that using the goodness‐of‐fit method (GOF) (Donner, Eliasziw, and Klar, 1996, Biometrics 52, 176–183). A simulation study for small and moderate sample sizes showed that the actual level of the homogeneity score test using the maximum likelihood estimators (MLEs) of parameters is satisfactorily close to the nominal and it is smaller than those of the modified homogeneity score and the goodness‐of‐fit tests. We investigated statistical properties of several noniterative estimators of a common kappa. The estimator (Donner et al., 1996) is essentially efficient and can be used as an alternative to the iterative MLE. An efficient interval estimation of a common kappa using the likelihood score method is presented.