title: Stepped wedge designs could reduce the required sample size in cluster randomized trials.
abstract: OBJECTIVE
  The stepped wedge design is increasingly being used in cluster randomized trials (CRTs). However, there is not much information available about the design and analysis strategies for these kinds of trials. Approaches to sample size and power calculations have been provided, but a simple sample size formula is lacking. Therefore, our aim is to provide a sample size formula for cluster randomized stepped wedge designs.
  
  
  METHODS
  We derived a design effect (sample size correction factor) that can be used to estimate the required sample size for stepped wedge designs. Furthermore, we compared the required sample size for the stepped wedge design with a parallel group and analysis of covariance (ANCOVA) design.
  
  
  RESULTS
  Our formula corrects for clustering as well as for the design. Apart from the cluster size and intracluster correlation, the design effect depends on choices of the number of steps, the number of baseline measurements, and the number of measurements between steps. The stepped wedge design requires a substantial smaller sample size than a parallel group and ANCOVA design.
  
  
  CONCLUSIONS
  For CRTs, the stepped wedge design is far more efficient than the parallel group and ANCOVA design in terms of sample size.
authors.affiliation: Department for Health Evidence, Radboud University Medical Centre, 133, PO Box 9101, 6500 HB Nijmegen, The Netherlands.
authors.forename: Willem
authors.initials: W
authors.lastname: Woertman
authors.forename: Esther
authors.initials: E
authors.lastname: de Hoop
authors.forename: Mirjam
authors.initials: M
authors.lastname: Moerbeek
authors.forename: Sytse U
authors.initials: SU
authors.lastname: Zuidema
authors.forename: Debby L
authors.initials: DL
authors.lastname: Gerritsen
authors.forename: Steven
authors.initials: S
authors.lastname: Teerenstra
mesh_terms: D000704:Analysis of Variance; D016010:Binomial Distribution; D016000:Cluster Analysis; D003198:Computer Simulation; D018592:Cross-Over Studies; D003863:Depression / Q000175:diagnosis* / Q000628:therapy*; D015340:Epidemiologic Research Design; D006801:Humans; D008432:Mathematical Computing; D016032:Randomized Controlled Trials as Topic / Q000379:methods* / Q000592:standards; D015203:Reproducibility of Results; D018401:Sample Size