Bayesian methods for estimating injury rates in sport injury epidemiology
Our findings indicate that the Bayesian framework naturally characterizes injury rates by modeling injury counts as outcomes of an underlying data-generation process that explicitly incorporates inherent uncertainty, complementing traditional frequentist approaches. Key benefits of the Bayesian approach in this context are the ability to test model suitability in a variety of methods, and to be able to generate plausible estimates with sparse data.
Authors
- Avinash Chandran (ORCID: https://orcid.org/0000-0002-2949-3668)
- Ben C. Lambert (ORCID: https://orcid.org/0000-0003-4274-4158)
Institutions
- University of Oxford (GB)
- Datalys Center for Sports Injury Research and Prevention (US)
Publication Details
- Journal
- Injury Epidemiology
- Published
- 2025-06-06
- DOI
- https://doi.org/10.1186/s40621-025-00583-z
- Citations
- 2
- Primary Topic
- Sports injuries and prevention
- Type
- article
- Field-Weighted Citation Impact
- 3.44
Funders
- National Collegiate Athletic Association