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http://hdl.handle.net/10071/10908
acessibilidade
Title: Improving the selection of pilot air force candidates using latent trajectories: an application of latent growth mixture modeling
Authors: Gomes, A.
Dias, J. G.
Issue Date: 2015
Publisher: Taylor and Francis
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.
Peer reviewed: yes
URI: http://hdl.handle.net/10071/10908
DOI: 10.1080/10508414.2015.1130489
ISSN: 1050-8414
Ciência-IUL: https://ciencia.iscte-iul.pt/id/ci-pub-28331
Accession number: WOS:000375234700004
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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