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» Step-Down FDR Procedures for Large Numbers of Hypotheses
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BMCBI
2007
120views more  BMCBI 2007»
13 years 5 months ago
Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures
Background: When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff be...
Xin Lu, David L. Perkins
BMCBI
2007
121views more  BMCBI 2007»
13 years 4 months ago
A constrained polynomial regression procedure for estimating the local False Discovery Rate
Background: In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (lFDR), which...
Cyril Dalmasso, Avner Bar-Hen, Philippe Broët
BMCBI
2008
122views more  BMCBI 2008»
13 years 4 months ago
Effects of dependence in high-dimensional multiple testing problems
Background: We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR) contro...
Kyung In Kim, Mark A. van de Wiel
CSDA
2008
102views more  CSDA 2008»
13 years 4 months ago
Step-up and step-down procedures controlling the number and proportion of false positives
In multiple hypotheses testing, it is important to control the probability of rejecting "true" null hypotheses. A standard procedure has been to control the family-wise ...
Paul N. Somerville, Claudia Hemmelmann