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|Title:||Improving the selection of pilot air force candidates using latent trajectories: an application of latent growth mixture modeling|
Dias, J. G.
|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.|
|Appears in Collections:||BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica|
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|Gomes_and_Dias__2016_.pdf||Versão Editora||661.88 kB||Adobe PDF||View/Open Request a copy|
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