Montagna, Silvia, Hopker, James G. (2018) A Bayesian approach to the use of athlete performance data within anti-doping. Frontiers in Physiology, 9 (884). ISSN 1664-042X. (doi:10.3389/fphys.2018.00884) (KAR id:67380)
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Official URL https://doi.org/10.3389/fphys.2018.00884 |
Abstract
The World Anti-doping Agency currently collates the results of all doping tests for
doping. Existing anti-doping strategies involve either the direct detection of use of
to their use. As the aim of any doping regime is to enhance athlete competitive
the fight against doping. In this regard, the identification of unexpected increases in
anti-doping testing programme. This study proposes a Bayesian framework for the
and limitations of such an approach. The Bayesian model was retrospectively applied to
the interindividual variability of intraindividual performance in order to create individualized
from athletes convicted for doping violations (3.69% of the sample) was used to assess
demonstrate the ability to detect performance differences (?1 m) between doped and
(i.e., doped vs. non-doped) with a high area under the curve (AUC = 0.97). However, the
non-doped athletes, misclassifying doped athletes as non-doped. This lack of sensitivity
and seasonality effects) potentially affecting performance into the framework. Further
and sensitivity.
Item Type: | Article |
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DOI/Identification number: | 10.3389/fphys.2018.00884 |
Subjects: | R Medicine > RC Internal medicine > RC1200 Sports medicine |
Divisions: | Divisions > Division of Natural Sciences > School of Sport and Exercise Sciences |
Depositing User: | James Hopker |
Date Deposited: | 20 Jun 2018 12:47 UTC |
Last Modified: | 16 Feb 2021 13:55 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/67380 (The current URI for this page, for reference purposes) |
Montagna, Silvia: | ![]() |
Hopker, James G.: | ![]() |
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