title: Against quantiles: categorization of continuous variables in epidemiologic research, and its discontents.
abstract: BACKGROUND
  Quantiles are a staple of epidemiologic research: in contemporary epidemiologic practice, continuous variables are typically categorized into tertiles, quartiles and quintiles as a means to illustrate the relationship between a continuous exposure and a binary outcome.
  
  
  CONCLUSIONS
  In this paper we argue that this approach is highly problematic and present several potential alternatives. We also discuss the perceived drawbacks of these newer statistical methods and the possible reasons for their slow adoption by epidemiologists.
  
  
  CONCLUSIONS
  The use of quantiles is often inadequate for epidemiologic research with continuous variables.
authors.affiliation: Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA 98195-7630, USA.
authors.forename: Caroline
authors.initials: C
authors.lastname: Bennette
authors.forename: Andrew
authors.initials: A
authors.lastname: Vickers
mesh_terms: D015982:Bias; D004059:Diffusion of Innovation; D015340:Epidemiologic Research Design; D006801:Humans; D015233:Models, Statistical; D018579:Patient Selection; D012307:Risk Factors; D012494:Sampling Studies