Statistics and Its Interface

Volume 7 (2014)

Number 1

We dedicate this special issue to Dr. Gang Zheng, a great colleague and dear friend to many of us.

Marginal analysis of measurement agreement among multiple raters with non-ignorable missing ratings

Pages: 113 – 120

DOI: http://dx.doi.org/10.4310/SII.2014.v7.n1.a12

Authors

Zhen Chen (Biostatistics and Bioinformatics Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, U.S.A.)

Yunlong Xie (Biostatistics and Bioinformatics Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, U.S.A.)

Abstract

In diagnostic medicine, several measurements have been developed to evaluate the agreements among raters when the data are complete. In practice, raters may not be able to give definitive ratings to some participants because symptoms may not be clear-cut. Simply removing subjects with missing ratings may produce biased estimates and result in loss of efficiency. In this article, we propose a within-cluster resampling (WCR) procedure and a marginal approach to handle non-ignorable missing data in measurement agreement data. Simulation studies show that both WCR and marginal approach provide unbiased estimates and have coverage probabilities close to the nominal level. The proposed methods are applied to a data set from the Physician Reliability Study in diagnosing endometriosis.

Keywords

Fleiss $\kappa$, Scott $\pi$, within-cluster resampling, marginal approach

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