A Non-iterative Confidence Interval Estimating Procedure for the Intraclass Kappa Statistic with Multinomial Outcomes

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Abstract

We obtain the asymptotic sample variance of the intraclass kappa statistic for multinomial outcome data. A modified Wald type procedure based on this theory is then used for confidence interval construction. The results of a simulation study show that the proposed non-iterative approach performs very well in terms of confidence interval coverage and width for samples as small as 50. The procedure is illustrated with two examples from previously published medical studies. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

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