articleInternational Journal of EpidemiologySep 1, 2017HYBRID OA

Collider scope: when selection bias can substantially influence observed associations

MRMarcus R. MunafòKTKate TillingAEAmy E. TaylorDMDavid M. EvansGDGeorge Davey Smith

MRC Epidemiology Unit · UK Centre for Tobacco & Alcohol Studies · +4 more institutions

PubMed
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Abstract

Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However, the representativeness of these samples may be limited-either through selection into studies, or by attrition from studies over time. Here we explore the potential impact of this selection bias on results obtained from these studies, from the perspective that this amounts to conditioning on a collider (i.e. a form of collider bias). Whereas it is acknowledged that selection bias will have a strong effect on representativeness and prevalence estimates, it is often assumed that it should not have a strong impact on estimates of associations. We argue that…

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Topics & keywords

Topics
Keywords
  • Collider
  • Selection bias
  • Selection (genetic algorithm)
  • Attrition
  • Representativeness heuristic
  • Population
  • Sampling bias
  • Sample size determination
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