Anti-Doping

A Bayesian approach to boost individual anti-doping classification accuracy by transverse monitoring of the athlete network

Purpose: To demonstrate a Bayesian approach utilizing the athlete network to boost the positive predictive value of individual doping classifications. Study Design and Methods:  Five data-sets of 10,000 individuals and their networks were simulated and statistically analyzed in R. Background prevalence (BP) of 10%, 20%, 30%, 40%, and 50% was chosen to cover the range …

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GoldenR Cheetah Script For Interval Discovery

The Golden Cheetah crew has now integrated R into Golden Cheetah in the latest development build. This update instantly gave Golden Cheetah statistical and modelling super-powers to the point where I gave it the nickname GoldenR Cheetah. As an example, this script uses the change point package to auto discover intervals within a power file. …

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Estimating the Probability of Doping as a Function of Power

A repeating theme heard in performance analysis discussions is that “Performance doesn’t prove doping.” Of course this is true because proof, as an absolute, doesn’t really exist. Instead, most real-world evidence driven judgments are based on probability and not “proof.” From this perspective, this post will illustrate the concept of using a mathematical model to …