title: An application of hierarchical regression in the investigation of multiple paternal occupational exposures and neuroblastoma in offspring.
abstract: BACKGROUND
  We used hierarchical regression to study the effects of 46 paternal occupational exposures on the incidence of neuroblastoma in offspring.
  
  
  METHODS
  The study population included 405 cases and 302 controls. The effect of each exposure was estimated using both conventional maximum likelihood and hierarchical regression.
  
  
  RESULTS
  Using hierarchical regression, overall precision was greatly enhanced compared to the conventional analysis. In addition, adjustment of effect estimates based on prespecified prior distributions of the true effect parameters allowed a more consistent interpretation across the entire panel of exposures. Estimates for several metals and solvents were shrunk close to the null value, whereas estimates for several thinner solvents, diesel fuel, solders, wood dust, and grain dust remained moderately elevated.
  
  
  CONCLUSIONS
  Hierarchical regression may mitigate some of the problems of the conventional approach by controlling for correlated exposures, enhancing the precision of estimates, and providing some adjustment of estimates based on prior knowledge.
authors.affiliation: Occupational Epidemiology Branch, National Cancer Institute, National Institutes of Health, Rockville, Maryland 20892-7240, USA. deroosa@mail.nih.gov
authors.forename: A J
authors.initials: AJ
authors.lastname: De Roos
authors.forename: C
authors.initials: C
authors.lastname: Poole
authors.forename: K
authors.initials: K
authors.lastname: Teschke
authors.forename: A F
authors.initials: AF
authors.lastname: Olshan
mesh_terms: D000328:Adult; D002648:Child; D006801:Humans; D015994:Incidence; D008297:Male; D009447:Neuroblastoma / Q000453:epidemiology*; D016273:Occupational Exposure; D018812:Paternal Exposure; D012044:Regression Analysis