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...

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Bibliographic Details
Published in:The International journal of aviation psychology 2014-04, Vol.24 (2), p.99-118
Main Authors: Weissmuller, Johnny J., Damos, Diane L.
Format: Article
Language:English
Subjects:
Classification
Comparative analysis
Computer simulation
Discriminant analysis
Logistics
Monte Carlo simulation
Pilot selection
Pilots
Regression
Regression analysis
Shortages
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Summary: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, we describe a selection system using a progressive process, rather than the traditional single- or multistage process. We discuss how system operators can adjust each of the processes to deal with a pilot shortage.
ISSN:1050-8414
1532-7108
DOI:10.1080/10508414.2014.892764