Adaptive selection of personality items to inform a neural network predicting job performance

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Adaptive selection of personality items to inform a neural network predicting job performance

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Title: Adaptive selection of personality items to inform a neural network predicting job performance
Author: Thissen-Roe, Anne
Abstract: Connectionist or "neural" networks, developed as a model of cognition, are also a general statistical model with practical applications. Adaptive testing, traditionally based on item response theory, is a way to improve the efficiency of a test. A hybrid system is developed that captures the main advantages of both technologies: the modeling flexibility of a neural network, and the efficiency gains of adaptive testing. A prototype is implemented for the case of a personality assessment used to predict job tenure at a national retail chain. Applicants' assessment and subsequent employment data are used to demonstrate the prototype's effectiveness.
Description: Thesis (Ph. D.)--University of Washington, 2005.
URI: http://hdl.handle.net/1773/9138

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