Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/10908
Author(s): | Gomes, A. Dias, J. G. |
Date: | 2015 |
Title: | Improving the selection of pilot air force candidates using latent trajectories: an application of latent growth mixture modeling |
Volume: | 25 |
Number: | 2 |
Pages: | 108 - 121 |
ISSN: | 1050-8414 |
DOI (Digital Object Identifier): | 10.1080/10508414.2015.1130489 |
Abstract: | Latent growth mixture modeling is a statistical approach that models longitudinal data, grouping individuals who share similar longitudinal data patterns into latent classes. We evaluated the application of this method in a sample of ab initio pilot applicants (N = 297), using longitudinal data collected from a military flight-screening program (where the applicants flew seven required flights), resulting in a final pass–fail outcome. Results showed the existence of a two-class solution (Cluster 1 presented an initially higher performance and contained 75% of the Pass candidates) and the psychomotor coordination and general adaptability showed a significant effect. |
Peerreviewed: | yes |
Access type: | Embargoed Access |
Appears in Collections: | BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Files in This Item:
File | Description | Size | Format | |
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Gomes_and_Dias__2016_.pdf Restricted Access | Versão Editora | 661,88 kB | Adobe PDF | View/Open Request a copy |
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