Abstract
A method is proposed for the analysis of nonagreements among multiple raters. The method is based on a notion of impartiality of nonagreeing assignments, and it aids in the detection of areas of possible confusion among different categories of a classification scale. A large-sample theory is derived for testing impartiality, and the methods are illustrated with published data on psychiatric classifications. Connections with kappa statistics for measuring rater agreement are also considered.
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