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Activity Number:
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403
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #300658 |
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Title:
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Estimating the Proportion of True Null Hypotheses Using the Pattern of the Observed P-Values
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Author(s):
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Tiejun Tong*+ and Zeny Feng and Hongyu Zhao
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Companies:
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University of Colorado, Boulder and University of Guelph and Yale University School of Medicine
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Address:
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Department of Applied Mathematics, Boulder, CO, 80309,
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Keywords:
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gene expression data ; multiple testing ; histogram ; p-value ; bootstrap
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Abstract:
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Estimating the proportion of true null hypotheses, $\pi_0$, has attracted much attention in the recent statistical literature. Besides its apparent relevance for a set of specific scientific hypotheses, an accurate estimate of this parameter is key for many multiple testing procedures. Most existing methods for estimating $\pi_0$ in the literature are motivated from the independence assumption of test statistics, which is often not the truth in reality. In this article, we propose a new method for estimating $\pi_0$ by incorporating the distribution pattern of the observed $p$-values as a practical approach to address potential dependence among test statistics. Simulations and real study indicate that the proposed method substantially decrease the variance and thus improve the overall performance.
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- Authors who are presenting talks have a * after their name.
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