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SUMMARY:Assessing the probability that a positive report is false: an appr
 oach for molecular epidemiology studies. - Gregor McCombie (Biochemistry D
 epartment\, Cambridge University)
DTSTART:20070928T130000Z
DTEND:20070928T140000Z
UID:TALK8058@talks.cam.ac.uk
CONTACT:Dr N Karp
DESCRIPTION:A presentation and discussion on the manuscript:J Natl Cancer 
 Inst. 2004 Mar 17\;96(6):434-42.\n\nAbstract: Too many reports of associat
 ions between genetic variants and common cancer sites and other complex di
 seases are false positives. A major reason for this unfortunate situation 
 is the strategy of declaring statistical significance based on a P value a
 lone\, particularly\, any P value below.05. The false positive report prob
 ability (FPRP)\, the probability of no true association between a genetic 
 variant and disease given a statistically significant finding\, depends no
 t only on the observed P value but also on both the prior probability that
  the association between the genetic variant and the disease is real and t
 he statistical power of the test. In this commentary\, we show how to asse
 ss the FPRP and how to use it to decide whether a finding is deserving of 
 attention or "noteworthy." We show how this approach can lead to improveme
 nts in the design\, analysis\, and interpretation of molecular epidemiolog
 y studies. Our proposal can help investigators\, editors\, and readers of 
 research articles to protect themselves from overinterpreting statisticall
 y significant findings that are not likely to signify a true association. 
 An FPRP-based criterion for deciding whether to call a finding noteworthy 
 formalizes the process already used informally by investigators--that is\,
  tempering enthusiasm for remarkable study findings with considerations of
  plausibility.\n\n
LOCATION:Meeting room 1 cambridge system biology centre
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