Modelling and prediction in recurrent time-to-event sports injury data: a penalized Cox regression approach

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  • Dae-Jin Lee (BCAM – Basque Center for Applied Statistics)
  • Local: ZOOM – 14:30 – Link – password: 242663
  • Quarta-feira, 22 de setembro de 2021
  • Seminário Conjunto CEAUL e CEMAT
  • Referência Projeto: UIDB/00006/2020 and UIDB/04621/2020

Sports injuries are complex phenomena that are a result of the dynamic interaction of multiple risk factors and have serious consequences on athletes’ health. Recently, statistical models are given special attention to the study of sports injuries to gain an in-depth understanding of its risk factors and mechanisms. In this talk, we evaluate statistical modelling strategies and methods based on the Cox regression model for high-dimensional data and recurrent injury data. Predictive performance is also studied via simulations. A real case study of injuries of female football players of a Spanish football club.