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Journal of the American Academy of Dermatology
Sous presse. Epreuves corrigées par l'auteur. Disponible en ligne depuis le mardi 12 novembre 2019
Doi : 10.1016/j.jaad.2019.07.061
Data dredging and false discovery

Dirk M. Elston, MD
 Department of Dermatology and Dermatologic Surgery, Medical University of South Carolina, Charleston, South Carolina 

Correspondence to: Dirk M. Elston, MD, Department of Dermatology and Dermatologic Surgery, Medical University of South Carolina, MSC 578, 135 Rutledge Ave, 11th Floor, Charleston, SC 29425-5780.Department of Dermatology and Dermatologic SurgeryMedical University of South CarolinaMSC 578, 135 Rutledge Ave, 11th FloorCharlestonSC29425-5780

 Funding sources: None.
 Conflicts of interest: None disclosed.

  The P value expresses the probability that the result occurred by chance alone, assuming that the null hypothesis is true. The level of significance, or alpha value , is associated with the confidence level of a test. For results with a 95% level of confidence, the alpha value is 0.05. The alpha value is the threshold that we measure P values against and gives the probability of a type I error (rejecting a null hypothesis that is actually true). When we set alpha at 0.05, the probability of a type I error (false-positive conclusion) is <5%. If the P value is less than or equal to alpha, there is reasonable certainty that the results did not occur by chance alone. A P value greater than alpha indicates a lack of statistical significance.
  False discovery rate is the ratio of false positive results to the number of total positive test results. The family-wise error rate is the combined probability of at least one false positive test.
  To calculate a Bonferroni-adjusted P value, divide the original alpha value by the number of analyses performed on the dependent variable. If thousands of analyses were performed, alpha becomes very small, and the P value must be equally small for results to be statistically significant. The Bonferroni correction reduces the risk of type I error but increases the risk of rejecting true discoveries.

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