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Prediction of injury risk in sports
Halmstad University, School of Health and Welfare, Centre of Research on Welfare, Health and Sport (CVHI), Health and Sport.ORCID iD: 0000-0002-8987-5975
Umeå University, Umeå, Sweden & University of Gothenburg, Gothenburg, Sweden & University of Otago, Dunedin, New Zealand.ORCID iD: 0000-0002-0834-1040
2019 (English)In: Wiley StatsRef: Statistics Reference Online / [ed] N. Balakrishnan, Theodore Colton, Brian Everitt, Walter Piegorsch, Fabrizio Ruggeri & Jozef L. Teugels, John Wiley & Sons, 2019Chapter in book (Refereed)
Abstract [en]

Sport injuries are a major problem associated with sport participation. To develop preventive strategies and programs, it is important to identify factors that will increase the likelihood of sport injuries. In most sport injury risk factor research, statistical analyses are performed; however, many of the most common statistical analyses provide limited information about predictors of sport injury risk. The common analyses used in previous studies do not acknowledge the complexity associated with investigating risk factors for sport injuries. To better capture this complexity, suggested in most theoretical frameworks, more appropriate of statistical approaches should be used. In this article we present how latent profile analysis, latent change score analysis, and latent growth curve analysis can be used to overcome some of the limitations with more traditional analyses. Lastly, we also elaborate on future directions for analyses in sport injury risk factor research. More specifically, we present how advanced statistical models, such as classification and regression trees (CART) analysis and random forest analysis, can be used to provide researchers and clinicians with results that are more clinically meaningful.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019.
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hh:diva-38528DOI: 10.1002/9781118445112.stat08141ISBN: 9781118445112 (electronic)OAI: oai:DiVA.org:hh-38528DiVA, id: diva2:1269177
Available from: 2018-12-09 Created: 2018-12-09 Last updated: 2022-09-06Bibliographically approved

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Ivarsson, AndreasStenling, Andreas

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf