General chance-corrected measures of agreement on individual subjects, for several observers using nominal or ordinal categories, are developed. The subject-specific measures can be used to identify subjects whom the observers find difficult to rate. The relationship of the subject-specific measures to a general chance-corrected measure of agreement for a group of subjects is demonstrated. By suitable choices of disagreement functions, the measure of agreement for a group of subjects is shown to include, as special cases, many of the kappa-like statistics. Also, it is asymptotically equivalent to various intraclass correlation coefficients. The measures do not require that the observers all use the classification scale in the same way. The asymptotic null and non-null variances obtained by Taylor-series approximations for the statistics are presented. The application of the measures is illustrated by data obtained when seven pathologists classified slides on a five-point ordinal scale for the diagnosis of carcinoma in situ of the uterine cervix.
Biometrics is a scientific journal emphasizing the role of statistics and mathematics in the biological sciences. Its object is to promote and extend the use of mathematical and statistical methods in pure and applied biological sciences by describing developments in these methods and their applications in a form readily assimilable by experimental scientists. JSTOR provides a digital archive of the print version of Biometrics. The electronic version of Biometrics is available at http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code;=biom. Authorized users may be able to access the full text articles at this site.
The International Biometric Society is an international society for the advancement of biological science through the development of quantitative theories and the application, development and dissemination of effective mathematical and statistical techniques. The Society welcomes as members biologists, mathematicians, statisticians, and others interested in applying similar techniques.
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Biometrics
© 1984 International Biometric Society
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