Statistical judgment formation in personnel selection: a study in military aviation psychology.

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 v...

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Publicado en:Military Psychology Vol. 19; no. 2; pp. 119 - 137
Autores principales: Arendasy M, Sommer M, Hergovich A
Formato: research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Apr2007
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Taylor & Francis Ltd
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        atl: Statistical judgment formation in personnel selection: a study in military aviation psychology.
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        au:
          Arendasy M
          Sommer M
          Hergovich A
        affil: Faculty of Psychology, University of Vienna, Vienna, Austria
      sug:
        subj:
          Military Personnel
          Neural Networks (Computer)
          Personnel Selection Methods
          Pilots
          Adolescence
          Adult
          Aptitude Tests
          Coefficient alpha
          Discriminant Analysis
          Germany
          Male
          Pilot Studies
          Scales
          Sensitivity and Specificity
          Human
          Adolescent: 13-18 years
          Adult: 19-44 years
          Male
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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