Improving the Pilot Selection System: Statistical Approaches and Selection Processes

摘要

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.