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Simultaneous Testing of Grouped Hypotheses: Finding Needles in Multiple Haystacks

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  • Cai, T. Tony
  • Sun, Wenguang

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  • 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.
    • Handle: RePEc:bes:jnlasa:v:104:i:488:y:2009:p:1467-1481
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    Cited by:

    1. Nikolaos Ignatiadis & Wolfgang Huber, 2021. "Covariate powered cross‐weighted multiple testing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 720-751, September.
    2. Habiger, Joshua D. & Peña, Edsel A., 2014. "Compound p-value statistics for multiple testing procedures," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 153-166.
    3. Alejandro Ochoa & John D Storey & Manuel Llinás & Mona Singh, 2015. "Beyond the E-Value: Stratified Statistics for Protein Domain Prediction," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-21, November.
    4. Hai Shu & Bin Nan & Robert Koeppe, 2015. "Multiple testing for neuroimaging via hidden Markov random field," Biometrics, The International Biometric Society, vol. 71(3), pages 741-750, September.
    5. Jiaying Gu & Roger Koenker, 2016. "On a Problem of Robbins," International Statistical Review, International Statistical Institute, vol. 84(2), pages 224-244, August.
    6. Otília Menyhart & Boglárka Weltz & Balázs Győrffy, 2021. "MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-12, June.
    7. Dennis Leung & Wenguang Sun, 2022. "ZAP: Z$$ Z $$‐value adaptive procedures for false discovery rate control with side information," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1886-1946, November.
    8. Simina M. Boca & Héctor Céorrada Bravo & Brian Caffo & Jeffrey T. Leek & Giovanni Parmigiani, 2013. "A Decision-Theory Approach to Interpretable Set Analysis for High-Dimensional Data," Biometrics, The International Biometric Society, vol. 69(3), pages 614-623, September.
    9. Zhao, Haibing & Fung, Wing Kam, 2016. "A powerful FDR control procedure for multiple hypotheses," Computational Statistics & Data Analysis, Elsevier, vol. 98(C), pages 60-70.
    10. T. Tony Cai & Wenguang Sun & Weinan Wang, 2019. "Covariate‐assisted ranking and screening for large‐scale two‐sample inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 187-234, April.
    11. Chen, Xiongzhi, 2019. "Uniformly consistently estimating the proportion of false null hypotheses via Lebesgue–Stieltjes integral equations," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 724-744.
    12. Joshua Habiger & David Watts & Michael Anderson, 2017. "Multiple testing with heterogeneous multinomial distributions," Biometrics, The International Biometric Society, vol. 73(2), pages 562-570, June.
    13. Zhao, Haibing, 2014. "Adaptive FWER control procedure for grouped hypotheses," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 63-70.
    14. Vincent, Kendro & Hsu, Yu-Chin & Lin, Hsiou-Wei, 2021. "Investment styles and the multiple testing of cross-sectional stock return predictability," Journal of Financial Markets, Elsevier, vol. 56(C).
    15. Li Wang, 2019. "Weighted multiple testing procedure for grouped hypotheses with k-FWER control," Computational Statistics, Springer, vol. 34(2), pages 885-909, June.
    16. Haibing Zhao & Xinping Cui, 2020. "Constructing confidence intervals for selected parameters," Biometrics, The International Biometric Society, vol. 76(4), pages 1098-1108, December.

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