| Sumario: | This study addresses the issue of data combination in personnel selection. In a pilot study for the selection of trainee pilots for the German Luftwaffe, 99 applicants were assessed using a comprehensive battery of tests that measured inductive thinking, spatial thinking, attentiveness, visual and verbal short-term memory, sensorimotor coordination, and reactive stress tolerance. The global evaluation of the applicants' performance in a flight simulator served as an external criterion. The predictive validity of this test battery was checked by carrying out a discriminant analysis as well as by calculating a neural network. The 2 methods were compared with regard to their classification rate, stability, and separation of correct and incorrect classifications. The results show that artificial neural networks are useful tools for improving the quality of selection procedures for trainee pilots.
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