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Adaptive FWER control procedure for grouped hypotheses

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  • Zhao, Haibing

Abstract

In this paper, we discuss the multiple testing problem for grouped hypotheses. We propose weighted p-value procedures, which are theoretically shown to control the family-wise error rate and be more powerful than existing methods. Simulation studies further confirm the theoretical analysis conclusions.

Suggested Citation

  • Zhao, Haibing, 2014. "Adaptive FWER control procedure for grouped hypotheses," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 63-70.
  • Handle: RePEc:eee:stapro:v:95:y:2014:i:c:p:63-70
    DOI: 10.1016/j.spl.2014.08.011
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    References listed on IDEAS

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    1. Cai, T. Tony & Sun, Wenguang, 2009. "Simultaneous Testing of Grouped Hypotheses: Finding Needles in Multiple Haystacks," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1467-1481.
    2. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    3. Wenge Guo, 2009. "A note on adaptive Bonferroni and Holm procedures under dependence," Biometrika, Biometrika Trust, vol. 96(4), pages 1012-1018.
    4. Christopher R. Genovese & Kathryn Roeder & Larry Wasserman, 2006. "False discovery control with p-value weighting," Biometrika, Biometrika Trust, vol. 93(3), pages 509-524, September.
    5. Hu, James X. & Zhao, Hongyu & Zhou, Harrison H., 2010. "False Discovery Rate Control With Groups," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1215-1227.
    6. Helmut Finner & Veronika Gontscharuk, 2009. "Controlling the familywise error rate with plug‐in estimator for the proportion of true null hypotheses," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(5), pages 1031-1048, November.
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    Cited by:

    1. Li Wang, 2019. "Weighted multiple testing procedure for grouped hypotheses with k-FWER control," Computational Statistics, Springer, vol. 34(2), pages 885-909, June.

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