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Abstract

We address the problem of selecting the best of a set of units based on a criterion variable, when its value is recorded for every unit subject to estimation, measurement, or another source of error. The solution is constructed in a decision-theoretical framework, incorporating the consequences (ramifications) of the various kinds of error that can be committed. The related problems of classifying the units to a small number of groups and ranking them are solved by a similar approach. An application is presented involving retention rates in the undergraduate courses of a university.

Keywords

classification decision theory empirical Bayes latent score league table loss function

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Decision Theory Applied to Selecting the Winners,Ranking,and Classification

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