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Improving the selection of pilot air force candidates using latent trajectories: an application of latent growth mixture modeling
Journal Title
International Journal of Aviation Psychology
Year (definitive publication)
2015
Language
English
Country
United States of America
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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.
Acknowledgements
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Keywords
Fields of Science and Technology Classification
- Psychology - Social Sciences
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| UID/GES/00315/2013 | Fundação para a Ciência e a Tecnologia |
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