Abstract
This paper focuses on the comparison between the optimal cutoff points set on single and multiple tests in predictor-based assessment, that is, assessing applicants as either suitable or unsuitable for a job. Our main result specifies the condition that determines the number of predictor tests, the collective assessment rule (aggregation procedure of predictor tests’ recommendations) and the function relating the tests’ assessment skills to the predictor cutoff points.
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© 2006 Springer-Verlag Berlin · Heidelberg
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Vos, H.J., Ben-Yashar, R., Nitzan, S. (2006). Comparing Optimal Individual and Collective Assessment Procedures. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_13
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DOI: https://doi.org/10.1007/3-540-34416-0_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34415-5
Online ISBN: 978-3-540-34416-2
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