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dc.contributor.advisorLee, Dae-Jin
dc.contributor.authorZumeta Olaskoaga, Lore
dc.date.accessioned2024-06-04T09:50:25Z
dc.date.available2024-06-04T09:50:25Z
dc.date.issued2024-02-16
dc.date.submitted2024-02-16
dc.identifier.urihttp://hdl.handle.net/10810/68336
dc.description193 p.es_ES
dc.description.abstractSports injuries stand as undesirable side effects of athletic participation, carrying serious consequencesfor athletes' health, their professional careers, and overall team performance. With the growing availability of data, there has been an increasing reliance on statistical models to monitor athletes' healthand mitigate injury risks.In this dissertation, our focus is on the statistical analysis of sports injury data, with an emphasis on the time-varying and recurrent nature of injury occurrences. We develop and assess suitable statistical modelling approaches to address specific research questions that arise in sports injury prevention research. We pursue three primary objectives: (a) identifying biomechanical risk factors using variableselection methods and shared frailty Cox models, (b) developing a flexible recurrent time-to-event approach to model the effects of training load on subsequent injuries, and (c) creating dedicated statistical tools through the open-source R software. These objectives are driven by interdisciplinary research, conducted in close collaboration with the Medical Services of Athletic Club, and are motivated by real-world applications. Namely, the work is based on three distinct data sets: the functional screening tests data, the external training load data, and the web-scraped football injury data. The statistical advancements developed contribute to ongoing efforts in sports injury prevention, providinginsights, methodologies, and accessible software implementations for sports medicine practitioners.es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-sa/3.0/es/*
dc.subjecttechniques of statistical associationes_ES
dc.titleStatistical Modelling for Recurrent Events in Sports Injury Research with Applications to Football InjuryData.es_ES
dc.typeinfo:eu-repo/semantics/doctoralThesises_ES
dc.rights.holderAtribución-CompartirIgual 3.0 España*
dc.rights.holder(cc)2024 LORE ZUMETA OLASKOAGA (cc by-sa 4.0)
dc.identifier.studentID698362es_ES
dc.identifier.projectID22688es_ES
dc.departamentoesMatemáticases_ES
dc.departamentoeuMatematikaes_ES


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Atribución-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Atribución-CompartirIgual 3.0 España