title: Centile charts II: alternative nonparametric approach for establishing time-specific reference centiles and assessment of the sample size required.
abstract: BACKGROUND
  Reference intervals, and more generally centile estimates, are used to characterize a reference population for the purposes of interpreting an individual patient's clinical measurement. We describe methods of calculating reference intervals where these centiles vary with a covariate, usually age or time.
  
  
  METHODS
  The US Food and Drug Administration and the IFCC have made recommendations on two approaches: the parametric approach, which models the structural characteristics of the data set with a theoretical distribution, and the nonparametric approach, which makes no particular assumption about this structure. In this report we propose a nonparametric procedure that relies on the principles of regression and show how sample size determination can be assessed. We also show how the sample size calculation is influenced by the distribution of the times measured.
  
  
  RESULTS
  We illustrated our method on three data sets and compared the results for our proposed nonparametric method with parametric estimates. We showed that the bias is reduced and that the nonparametric method is less likely to produce fluctuating profiles.
  
  
  CONCLUSIONS
  To achieve adequate precision the sample size needs to be larger than 120, as has often been recommended. If there is doubt about the parametric model, then threshold sample sizes may need to be as high as 500.
authors.affiliation: Department of Epidemiology, Statistics and Public Health, University of Wales College of Medicine, Heath Park, Cardiff, United Kingdom.
authors.forename: Jenny K
authors.initials: JK
authors.lastname: Griffiths
authors.forename: Terence C
authors.initials: TC
authors.lastname: Iles
authors.forename: Martin
authors.initials: M
authors.lastname: Koduah
authors.forename: Arthur B J
authors.initials: AB
authors.lastname: Nix
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000704:Analysis of Variance; D001724:Birth Weight; D002648:Child; D002784:Cholesterol / Q000097:blood; D019411:Clinical Laboratory Techniques / Q000706:statistics & numerical data*; D003430:Cross-Sectional Studies; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D007668:Kidney / Q000033:anatomy & histology; D008875:Middle Aged; D011247:Pregnancy; D012016:Reference Values; D012044:Regression Analysis; D018401:Sample Size; D018709:Statistics, Nonparametric; D013997:Time Factors; D000509:alpha-Fetoproteins / Q000032:analysis
chemical_list: D000509:alpha-Fetoproteins; D002784:Cholesterol