The science of doping

  title={The science of doping},
  author={Donald A. Berry},
  • D. Berry
  • Published 6 August 2008
  • Psychology, Medicine
  • Nature
The processes used to charge athletes with cheating are often based on flawed statistics and flawed logic, says Donald A. Berry. 
Un-Kultur: Doping im (Hochleistungs)Sport
Der Autor dieses Beitrags beschaftigt sich seit ziemlich genau 25 Jahren aus sozialwissenschaftlicher Sicht mit dem Phanomen des Dopings im Leistungs-Sport.
Anti-doping researchers should conform to certain statistical standards from forensic science.
  • Klaas Faber, M. Sjerps
  • Sociology, Medicine
    Science & justice : journal of the Forensic Science Society
  • 2009
Close examination shows that the statistical treatment of evidence is inconsistent with the view that anti-doping is currently viewed as a forensic science.
Tacit premises and assumptions in anti-doping research
Abstract The development of the Anti-Doping Test Regime over the last few decades has been described as a process of increasing restrictions to athletes’ civil rights. This process is based on two
Professional Cycling and the Fight against Doping
Doping seems to be well-organized and inherent in the system of professional cycling. This paper provides a theoretical approach, by using a multi-task (training and doping) principal-agent (team
'Clean athlete status' cannot be certified: Calling for caution, evidence and transparency in 'alternative' anti-doping systems.
The Clean Protocol™ is scrutinised, which is the most comprehensive alternative system, for its shortcomings through detailed analysis of its alleged logical and scientific merits, and argues that whilst protecting clean sport is critically important to all stakeholders, protocols that put athletes in disadvantageous positions and/or pose risks to their professional and personal lives lack legitimacy.
How to produce the belief in clean sports which sells
Abstract Organisers of sport competitions sell a product, consisting of athletes’ performance and integrity of competition. These components are consumed simultaneously. Consumer demand for elite
Substance Identification in Anti-Doping Control by Means of Mass Spectrometry. Data Reduction and Decision Criteria
A real doping case for which the national-level reviewing body deemed it probable that a misidentification of the national-level athlete’s sample occurred at the WADA accredited laboratory, thus
Antidoping Science: Important Lessons From the Medical Sciences.
It is shown how the validity of doping tests are neither "stand-alone figures" generated under ideal laboratory conditions, nor figures that can be used in isolation to support the efficacy of the current drug testing program.
Doping in Two Elite Athletics Competitions Assessed by Randomized-Response Surveys
Doping appears remarkably widespread among elite athletes, and remains largely unchecked despite current biological testing, according to a randomized response technique used to estimate the prevalence of doping.
Qualitative evidence of a primary intervention point for elite athlete doping.
The findings indicate primary prevention of doping may be enhanced by timing it around periods of career instability where athlete vulnerability to doping may increase as a function of winning or losing sponsorship.


Inferences about Testosterone Abuse among Athletes
There is no "gold standard" when testing for substance abuse, and the appropriate tool for decision making under uncertainty is Bayes' Mary Decker Slaney at the 1996 Sumrule.
The Prosecutor's Fallacy and the Defense Attorney's Fallacy*
In criminal cases where the evidence shows a match between the defendant and the perpetrator on some characteristic, the jury often receives statistical evidence on the incidence rate of the
Inferences Using DNA Profiling in Forensic Identification and Paternity Cases
Forensic laboratories use lengths of fragments from several locations of human DNA to decide whether a sample of body fluid left at the scene of a crime came from a suspect or whether a sample
Statistics: A Bayesian Perspective
1. Statistics and the Scientific Method 2. Displaying and Summarizing Data 3. Designing Experiments 4. Probability and Uncertainty 5. Conditional Probability and Bayes' Rule 6. Models for Proportions