An Evaluation of Backpropagation Neural Network Modeling as an Alternative Methodology for Criterion Validation of Employee Selection Testing

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Description

Employee selection research identifies and makes use of associations between individual differences, such as those measured by psychological testing, and individual differences in job performance. Artificial neural networks are computer simulations of biological nerve systems that can be used to model unspecified relationships between sets of numbers. Thirty-five neural networks were trained to estimate normalized annual revenue produced by telephone sales agents based on personality and biographic predictors using concurrent validation data (N=1085). Accuracy of the neural estimates was compared to OLS regression and a proprietary nonlinear model used by the participating company to select agents.

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xiv, 334 leaves : ill.

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Scarborough, David J. (David James) August 1995.

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  • Scarborough, David J. (David James)

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Employee selection research identifies and makes use of associations between individual differences, such as those measured by psychological testing, and individual differences in job performance. Artificial neural networks are computer simulations of biological nerve systems that can be used to model unspecified relationships between sets of numbers. Thirty-five neural networks were trained to estimate normalized annual revenue produced by telephone sales agents based on personality and biographic predictors using concurrent validation data (N=1085). Accuracy of the neural estimates was compared to OLS regression and a proprietary nonlinear model used by the participating company to select agents.

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xiv, 334 leaves : ill.

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  • August 1995

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  • March 24, 2014, 8:07 p.m.

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  • March 31, 2015, 2:18 p.m.

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Citations, Rights, Re-Use

Scarborough, David J. (David James). An Evaluation of Backpropagation Neural Network Modeling as an Alternative Methodology for Criterion Validation of Employee Selection Testing, dissertation, August 1995; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc277752/: accessed November 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .