title: A priori postulated and real power in cluster randomized trials: mind the gap.
abstract: BACKGROUND
  Cluster randomization design is increasingly used for the evaluation of health-care, screening or educational interventions. The intraclass correlation coefficient (ICC) defines the clustering effect and be specified during planning. The aim of this work is to study the influence of the ICC on power in cluster randomized trials.
  
  
  METHODS
  Power contour graphs were drawn to illustrate the loss in power induced by an underestimation of the ICC when planning trials. We also derived the maximum achievable power given a specified ICC.
  
  
  RESULTS
  The magnitude of the ICC can have a major impact on power, and with low numbers of clusters, 80% power may not be achievable.
  
  
  CONCLUSIONS
  Underestimating the ICC during planning cluster randomized trials can lead to a seriously underpowered trial. Publication of a priori postulated and a posteriori estimated ICCs is necessary for a more objective reading: negative trial results may be the consequence of a loss of power due to a mis-specification of the ICC.
authors.affiliation: Département d'Epidémiologie, Biostatistique et Recherche Clinique, Groupe Hospitalier Bichat-Claude Bernard (AP-HP) - Université Paris 7, Paris, France. lguittet@free.fr
authors.forename: Lydia
authors.initials: L
authors.lastname: Guittet
authors.forename: Bruno
authors.initials: B
authors.lastname: Giraudeau
authors.forename: Philippe
authors.initials: P
authors.lastname: Ravaud
mesh_terms: D016000:Cluster Analysis; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D003662:Decision Theory; D005843:Geography; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data; D012107:Research Design / Q000706:statistics & numerical data