title: Sample size determination for the false discovery rate.
abstract: BACKGROUND
  There is not a widely applicable method to determine the sample size for experiments basing statistical significance on the false discovery rate (FDR).
  
  
  RESULTS
  We propose and develop the anticipated FDR (aFDR) as a conceptual tool for determining sample size. We derive mathematical expressions for the aFDR and anticipated average statistical power. These expressions are used to develop a general algorithm to determine sample size. We provide specific details on how to implement the algorithm for a k-group (k > or = 2) comparisons. The algorithm performs well for k-group comparisons in a series of traditional simulations and in a real-data simulation conducted by resampling from a large, publicly available dataset.
  
  
  BACKGROUND
  Documented S-plus and R code libraries are freely available from www.stjuderesearch.org/depts/biostats.
authors.affiliation: Department of Biostatistics, St Jude Children's Research Hospital 332 N. Lauderdale Street, Memphis, TN 38135, USA. stanley.pounds@stjude.org
authors.forename: Stan
authors.initials: S
authors.lastname: Pounds
authors.forename: Cheng
authors.initials: C
authors.lastname: Cheng
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D030562:Databases, Protein; D005189:False Positive Reactions; D020869:Gene Expression Profiling; D008957:Models, Genetic; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D015203:Reproducibility of Results; D018401:Sample Size; D012984:Software