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Recently, there has been an increasing level of interest in subscores for their potential diagnostic value. Haberman suggested a method based on classical test theory to determine whether subscores have added value over total scores. In this article I first provide a rich collection of results regarding when subscores were found to have added value for several operational data sets. Following that I provide results from a detailed simulation study that examines what properties subscores should possess in order to have added value. The results indicate that subscores have to satisfy strict standards of reliability and correlation to have added value. A weighted average of the subscore and the total score was found to have added value more often.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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