A sequential test for assessing observed agreement between raters |
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| Authors: | Sotiris Bersimis Athanasios Sachlas Subha Chakraborti |
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| Affiliation: | 1. Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece;2. Department of Information Systems, Statistics and Management Science, University of Alabama, AL, USA |
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| Abstract: | Assessing the agreement between two or more raters is an important topic in medical practice. Existing techniques, which deal with categorical data, are based on contingency tables. This is often an obstacle in practice as we have to wait for a long time to collect the appropriate sample size of subjects to construct the contingency table. In this paper, we introduce a nonparametric sequential test for assessing agreement, which can be applied as data accrues, does not require a contingency table, facilitating a rapid assessment of the agreement. The proposed test is based on the cumulative sum of the number of disagreements between the two raters and a suitable statistic representing the waiting time until the cumulative sum exceeds a predefined threshold. We treat the cases of testing two raters' agreement with respect to one or more characteristics and using two or more classification categories, the case where the two raters extremely disagree, and finally the case of testing more than two raters' agreement. The numerical investigation shows that the proposed test has excellent performance. Compared to the existing methods, the proposed method appears to require significantly smaller sample size with equivalent power. Moreover, the proposed method is easily generalizable and brings the problem of assessing the agreement between two or more raters and one or more characteristics under a unified framework, thus providing an easy to use tool to medical practitioners. |
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| Keywords: | agreement assessment Cohen's k hypothesis testing Markov chain embedding technique sequential testing |
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