title: Data adaptive interim modification of sample sizes for candidate-gene association studies.
abstract: OBJECTIVE
  The use of conventional Transmission/Disequilibrium tests in the analysis of candidate-gene association studies requires the precise and complete pre-specification of the total number of trios to be sampled to obtain sufficient power at a certain significance level (type I error risk). In most of these studies, very little information about the genetic effect size will be available beforehand and thus it will be difficult to calculate a reasonable sample size. One would therefore wish to reassess the sample size during the course of a study.
  
  
  METHODS
  We propose an adaptive group sequential procedure which allows for both early stopping of the study with rejection of the null hypothesis (H0) and for recalculation of the sample size based on interim effect size estimates when H0 cannot be rejected. The applicability of the method which was developed by Müller and Schäfer [Biometrics 2001;57:886-891] in a clinical context is demonstrated by a numerical example. Monte Carlo simulations are performed comparing the adaptive procedure with a fixed sample and a conventional group sequential design.
  
  
  RESULTS
  The main advantage of the adaptive procedure is its flexibility to allow for design changes in order to achieve a stabilized power characteristic while controlling the overall type I error and using the information already collected.
  
  
  CONCLUSIONS
  Given these advantages, the procedure is a promising alternative to traditional designs.
authors: Institute of Medical Biometry and Epidemiology, Clinic of Child and Adolescent Psychiatry, University of Marburg, Germany.
authors: André
authors: A
authors: Scherag
authors: Hans-Helge
authors: HH
authors: Müller
authors: Astrid
authors: A
authors: Dempfle
authors: Johannes
authors: J
authors: Hebebrand
authors: Helmut
authors: H
authors: Schäfer
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D008957:Models, Genetic; D009010:Monte Carlo Method; D018401:Sample Size