title: Testing multiple statistical hypotheses resulted in spurious associations: a study of astrological signs and health.
abstract: OBJECTIVE
  To illustrate how multiple hypotheses testing can produce associations with no clinical plausibility.
  
  
  METHODS
  We conducted a study of all 10,674,945 residents of Ontario aged between 18 and 100 years in 2000. Residents were randomly assigned to equally sized derivation and validation cohorts and classified according to their astrological sign. Using the derivation cohort, we searched through 223 of the most common diagnoses for hospitalization until we identified two for which subjects born under one astrological sign had a significantly higher probability of hospitalization compared to subjects born under the remaining signs combined (P<0.05).
  
  
  RESULTS
  We tested these 24 associations in the independent validation cohort. Residents born under Leo had a higher probability of gastrointestinal hemorrhage (P=0.0447), while Sagittarians had a higher probability of humerus fracture (P=0.0123) compared to all other signs combined. After adjusting the significance level to account for multiple comparisons, none of the identified associations remained significant in either the derivation or validation cohort.
  
  
  CONCLUSIONS
  Our analyses illustrate how the testing of multiple, non-prespecified hypotheses increases the likelihood of detecting implausible associations. Our findings have important implications for the analysis and interpretation of clinical studies.
authors.affiliation: Institute for Clinical Evaluative Sciences, G1 06, 2075 Bayview Avenue, Toronto, Ontario, M4N 3M5 Canada. peter.austin@ices.on.ca
authors.forename: Peter C
authors.initials: PC
authors.lastname: Austin
authors.forename: Muhammad M
authors.initials: MM
authors.lastname: Mamdani
authors.forename: David N
authors.initials: DN
authors.lastname: Juurlink
authors.forename: Janet E
authors.initials: JE
authors.lastname: Hux
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001255:Astrology; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D004198:Disease Susceptibility; D019317:Evidence-Based Medicine / Q000706:statistics & numerical data*; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D009864:Ontario