Improving the Pilot Selection System: Statistical Approaches and Selection Processes

Pilot selection systems traditionally use one of three statistical approaches to model candidate performance: multiple linear regression, linear discriminant analysis, and logistic regression. This article reviews the literature comparing selection decisions using these three approaches and compares the classification accuracy of linear discriminant analysis and logistic regression to the results from two Monte Carlo simulations. Methods for adjusting to a pilot shortage are described for each statistical approach. In the second half of the article, the authors describe a selection system using a progressive process, rather than the traditional single- or multistage process. They discuss how system operators can adjust each of the processes to deal with a pilot shortage.

• Record URL:
  • https://doi.org/10.1080/10508414.2014.892764
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/21653673
• Supplemental Notes:
  • Abstract reprinted with permission from Taylor and Francis.
• Authors:
  • Weissmuller, Johnny J
  • Damos, Diane L
• Publication Date: 2014-4

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 99-118
• Serial:
  • International Journal of Aviation Psychology
  • Volume: 24
  • Issue Number: 2
  • Publisher: Taylor & Francis
  • ISSN: 1050-8414
  • EISSN: 1532-7108
  • Serial URL: http://www.tandfonline.com/toc/hiap20/current

Subject/Index Terms

• TRT Terms: Air pilots; Discriminant analysis; Linear regression analysis; Logistic regression analysis; Monte Carlo method; Selection and appointment
• Subject Areas: Administration and Management; Aviation; I10: Economics and Administration;

Filing Info

• Accession Number: 01526114
• Record Type: Publication
• Files: TRIS
• Created Date: May 28 2014 3:24PM