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False Discovery Control for Multiple Tests of Association Under General Dependence

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  • NICOLAI MEINSHAUSEN

Abstract

. We propose a confidence envelope for false discovery control when testing multiple hypotheses of association simultaneously. The method is valid under arbitrary and unknown dependence between the test statistics and allows for an exploratory approach when choosing suitable rejection regions while still retaining strong control over the proportion of false discoveries.

Suggested Citation

  • Nicolai Meinshausen, 2006. "False Discovery Control for Multiple Tests of Association Under General Dependence," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 227-237, June.
    • Handle: RePEc:bla:scjsta:v:33:y:2006:i:2:p:227-237
    DOI: 10.1111/j.1467-9469.2005.00488.x
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    Cited by:

    1. Axel Gandy & Georg Hahn, 2016. "A Framework for Monte Carlo based Multiple Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1046-1063, December.
    2. Axel Gandy & Georg Hahn, 2014. "MMCTest—A Safe Algorithm for Implementing Multiple Monte Carlo Tests," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1083-1101, December.
    3. Jesse Hemerik & Jelle Goeman, 2018. "Exact testing with random permutations," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(4), pages 811-825, December.
    4. Aldo Solari & Livio Finos & Jelle J. Goeman, 2014. "Rotation-based multiple testing in the multivariate linear model," Biometrics, The International Biometric Society, vol. 70(4), pages 954-961, December.
    5. Guillermo Durand & Gilles Blanchard & Pierre Neuvial & Etienne Roquain, 2020. "Post hoc false positive control for structured hypotheses," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1114-1148, December.

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