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Challenges with Confidence Intervals for Sport Injury Burden, other Ratio Measures and Clustered data

An evaluation of recent practices

##article.authors##

  • Ian Shrier Centre for Clinical Epidemiology, Lady Davis Institute, McGill University
  • Franco M. Impellizzeri
  • Avinash Chandran
  • Sean Williams
  • Joseph W. Shaw
  • Russell J. Steele

DOI:

https://doi.org/10.51224/SRXIV.546

Keywords:

confidence interval, bootstrap, standard error, injury burden, injury incidence

Abstract

Several studies investigating injury burden have used “standard” formulae for injury rates when calculating their 95% confidence intervals. However, this may have led to artificially narrow confidence intervals because the authors’ calculations did not account for (1) violations of important underlying assumptions, and (2) the same athlete having multiple injuries. Although previous authors have recommended appropriate methods such as bootstrapping to solve the first challenge, there is little guidance for sport medicine researchers on how to implement bootstrapping given the complexity of data in our field. The purposes of this article are (1) to illustrate when the “standard” formulae for injury rate confidence intervals can be used in sport medicine research, (2) why the standard formulae for injury rate confidence intervals are inappropriate when estimating injury burden and (3) provide more detailed instructions on how to use bootstrapping for confidence intervals in the context of any sport medicine study that includes repeated measures.

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Posted

2025-05-08 — Updated on 2025-05-28

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