title: Assessing the suitability of fractional polynomial methods in health services research: a perspective on the categorization epidemic.
abstract: OBJECTIVE
  To show how fractional polynomial methods can usefully replace the practice of arbitrarily categorizing data in epidemiology and health services research.
  
  
  METHODS
  A health service setting is used to illustrate a structured and transparent way of representing non-linear data without arbitrary grouping.
  
  
  RESULTS
  When age is a regressor its effects on an outcome will be interpreted differently depending upon the placing of cutpoints or the use of a polynomial transformation.
  
  
  CONCLUSIONS
  Although it is common practice, categorization comes at a cost. Information is lost, and accuracy and statistical power reduced, leading to spurious statistical interpretation of the data. The fractional polynomial method is widely supported by statistical software programs, and deserves greater attention and use.
authors.affiliation: Research Centre for Gender, Health and Ageing, Newcastle Institute of Public Health, University of Newcastle, Newcastle, Australia. Jenny.stewartwilliams@newcastle.edu.au
authors.forename: Jennifer Stewart
authors.initials: JS
authors.lastname: Williams
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000072038:Cardiac Rehabilitation; D003627:Data Interpretation, Statistical; D006302:Health Services Research / Q000379:methods*; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D012107:Research Design