Sample size determination for the false discovery rate.

Bioinformatics 2005 Dec 4;21(23):4263-71. Epub 2005 Oct 4.

Department of Biostatistics, St Jude Children's Research Hospital 332 N. Lauderdale Street, Memphis, TN 38135, USA.

Motivation: 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.

Availability: Documented S-plus and R code libraries are freely available from www.stjuderesearch.org/depts/biostats.

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Source
https://academic.oup.com/bioinformatics/article-lookup/doi/1
Publisher Site
http://dx.doi.org/10.1093/bioinformatics/bti699DOI Listing
December 2005
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