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Multiple hypotheses testing is a core problem in statistical inference and arises in almost every scientific field.
Controlling the false discovery rate: a practical and powerful approach to multiple testing
Y. Benjamini and Y. Hochberg · 1995
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Adaptive sample size calculations in group sequential trials
W. Lehmacher and G. Wassmer · 1999
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The control of the false discovery rate in multiple testing under dependency
Y. Benjamini and D. Yekutieli · 2001
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Gene expression correlates of clinical prostate cancer behavior
D. Singh, P. G. Febbo, K. Ross, D. G. Jackson, J. Manola, C. Ladd, P. Tamayo, A. A. Renshaw, A. V. D’Amico, J. P. Richie, et al · 2002
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Contradicted and initially stronger effects in highly cited clinical research
J. P. Ioannidis · 2005
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Why most published research findings are false
J. P. Ioannidis · 2005
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Alpha-investing: A procedure for sequential control of expected false discoveries
D. P. Foster and R. A. Stine · 2007
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Probability: theory and examples
R. Durrett · 2010
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Vif regression: A fast regression algorithm for large data
D. Lin, D. P. Foster, and L. H. Ungar · 2011
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Believe it or not: how much can we rely on published data on potential drug targets?
F. Prinz, T. Schlange, and K. Asadullah · 2011
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Sequential selection procedures and false discovery rate control
M. G. G’Sell, S. Wager, A. Chouldechova, and R. Tibshirani · 2013
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Nearly optimal sample size in hypothesis testing for high-dimensional regression
A. Javanmard and A. Montanari · 2013
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Generalized α \alpha -investing: definitions, optimality results and application to public databases
E. Aharoni and S. Rosset · 2014
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Optimal inference after model selection
W. Fithian, D. Sun, and J. Taylor · 2014
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Confidence intervals and hypothesis testing for high-dimensional regression
A. Javanmard and A. Montanari · 2014
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Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory
A. Javanmard and A. Montanari · 2014
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A significance test for the lasso
R. Lockhart, J. Taylor, R. J. Tibshirani, and R. Tibshirani · 2014
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Novel statistical tools for management of public databases facilitate community-wide replicability and control of false discovery
S. Rosset, E. Aharoni, and H. Neuvirth · 2014
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M. Bogdan, E. v. d. Berg, C. Sabatti, W. Su, and E. J. Candes · 2014
Cited alongside, same era.
Controlling the false discovery rate via knockoffs
R. F. Barber and E. Candes · 2014
Cited alongside, same era.
Preserving statistical validity in adaptive data analysis
C. Dwork, V. Feldman, M. Hardt, T. Pitassi, O. Reingold, and A. Roth · 2014
Cited alongside, same era.
J. Taylor, R. Lockhart, R. J. Tibshirani, and R. Tibshirani · 2014
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On asymptotically optimal confidence regions and tests for high-dimensional models
S. Van de Geer, P. Bühlmann, Y. Ritov, R. Dezeure, et al · 2014
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Confidence intervals for low dimensional parameters in high dimensional linear models
C.-H. Zhang and S. S. Zhang · 2014
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