Literature DB >> 16204346

Sample size determination for the false discovery rate.

Stan Pounds1, Cheng Cheng.   

Abstract

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.

Mesh:

Year:  2005        PMID: 16204346     DOI: 10.1093/bioinformatics/bti699

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  25 in total

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3.  Practical guidelines for assessing power and false discovery rate for a fixed sample size in microarray experiments.

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5.  A procedure to statistically evaluate agreement of differential expression for cross-species genomics.

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6.  Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms.

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7.  Gene expression profiling in whole blood of patients with coronary artery disease.

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Review 8.  Microproteomics: analysis of protein diversity in small samples.

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9.  Power and sample size estimation in microarray studies.

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Journal:  BMC Bioinformatics       Date:  2010-01-25       Impact factor: 3.169

10.  A simulation-approximation approach to sample size planning for high-dimensional classification studies.

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Journal:  Biostatistics       Date:  2009-02-21       Impact factor: 5.899

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