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Generalized Augmentation to Control the False Discovery Exceedance in Multiple Testing

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  • ALESSIO FARCOMENI

Abstract

A new multiple testing procedure, the generalized augmentation procedure (GAUGE), is introduced. The procedure is shown to control the false discovery exceedance and to be competitive in terms of power. It is also shown how to apply the idea of GAUGE to achieve control of other error measures. Extensions to dependence are discussed, together with a modification valid under arbitrary dependence. We present an application to an original study on prostate cancer and on a benchmark data set on colon cancer. Copyright (c) 2009 Board of the Foundation of the Scandinavian Journal of Statistics.

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  • Alessio Farcomeni, 2009. "Generalized Augmentation to Control the False Discovery Exceedance in Multiple Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 501-517.
  • Handle: RePEc:bla:scjsta:v:36:y:2009:i:3:p:501-517
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    Cited by:

    1. Cerioli, Andrea & Farcomeni, Alessio, 2011. "Error rates for multivariate outlier detection," Computational Statistics & Data Analysis, Elsevier, pages 544-553.
    2. Thorsten Dickhaus, 2012. "Simultaneous Statistical Inference in Dynamic Factor Models," SFB 649 Discussion Papers SFB649DP2012-033, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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