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  \textbf{\Large{\textsc{STANFORD UNIVERSITY}}}\\[5pt]
  \textbf{\Large{\textsc{DEPARTMENT OF STATISTICS}}}\\[5pt]
  \Large{\textsc{DEPARTMENTAL SEMINAR}}
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  4:15 p.m., Tuesday, May 08, 2007\\
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  Sequoia Hall Room 200\\
  (Cookies at 3:45 in 1st Floor Lounge)
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  \textsl{M.B. Rao} \\
  Center for Genome Information\\
  University of Cincinnati
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  \subsection*{On the Control of False Discovery Rate with no Assumption of 
  Dependency}
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\noindent

In first part of the lecture, issues and ideas surrounding multiple testing of 
hypotheses will be discussed. Then the focus will be on the Bejamini-Hochberg 
step-up procedure. An upper bound for the False Discovery Rate (FDR) has been 
established by Benjamini and Yekutieli no matter what the joint distribution of 
the underlying p-values is. We point out that this upper bound can not be 
improved in the sense that there is a joint distribution of p-values for which 
the upper bound is attained. We present a step-down procedure for which the 
upper bound is lower than that given by Benjamini and Yekutieli. Practical 
implications of this result will be discussed.  


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