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To perform inference after model selection, we propose controlling the selective type I error; i.e., the error rate of a test given that it was performed.
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False discovery rate–adjusted multiple confidence intervals for selected parameters
Yoav Benjamini and Daniel Yekutieli · 2005
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Why most published research findings are false
John PA Ioannidis · 2005
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Model selection and inference: Facts and fiction
Hannes Leeb and Benedikt M Pötscher · 2005
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Testing statistical hypotheses
EL Lehmann and Joseph P Romano · 2005
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Drop-the-losers design: Normal case
Allan R Sampson and Michael W Sill · 2005
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Can one estimate the conditional distribution of post-model-selection estimators?
Hannes Leeb and Benedikt M Pötscher · 2006
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Inference on treatment effects after selection among high-dimensional controls
Alexandre Belloni, Victor Chernozhukov, and Christian Hansen · 2014
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Publication bias in the social sciences: unlocking the file drawer
Annie Franco, Neil Malhotra, and Gabor Simonovits · 2014
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Visualizing lasso polytope geometry, June 2014
Naftali Harris · 2014
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Hypothesis testing in high-dimensional regression under the gaussian random design model: Asymptotic theory
Adel Javanmard and Andrea Montanari · 2014
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New truths that only one can see
George Johnson · 2014
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Exact post model selection inference for marginal screening
Jason D Lee and Jonathan E Taylor · 2014
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A genome-wide association study identifies novel risk loci for type 2 diabetes
Robert Sladek, Ghislain Rocheleau, Johan Rung, Christian Dina, Lishuang Shen, David Serre, Philippe Boutin, Daniel Vincent, Alexandre Belisle, Samy Hadjadj, et al · 2007
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Overcoming the winner’s curse: estimating penetrance parameters from case-control data
Sebastian Zöllner and Jonathan K Pritchard · 2007
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Can one estimate the unconditional distribution of post-model-selection estimators?
Hannes Leeb and Benedikt M Pötscher · 2008
Cited alongside, same era.
Bias-reduced estimators and confidence intervals for odds ratios in genome-wide association studies
Hua Zhong and Ross L Prentice · 2008
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The elements of statistical learning , volume 2
Trevor Hastie, Robert Tibshirani, Jerome Friedman, T Hastie, J Friedman, and R Tibshirani · 2009
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P-values for high-dimensional regression
Nicolai Meinshausen, Lukas Meier, and Peter Bühlmann · 2009
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A significance test for the lasso (with discussion)
Richard Lockhart, Jonathan Taylor, Ryan J Tibshirani, and Robert Tibshirani · 2014
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A significance test for forward stepwise model selection
Joshua R Loftus and Jonathan E Taylor · 2014
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Exact hamiltonian monte carlo for truncated multivariate gaussians
Ari Pakman and Liam Paninski · 2014
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Selective correlations; not voodoo
JD Rosenblatt and Yoav Benjamini · 2014
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Exact post-selection inference for sequential regression procedures
Ryan J Tibshirani, Jonathan Taylor, Richard Lockhart, and Robert Tibshirani · 2014
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On asymptotically optimal confidence regions and tests for high-dimensional models
Sara Van de Geer, Peter Bühlmann, Ya’acov Ritov, Ruben Dezeure, et al · 2014
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Confidence intervals for low dimensional parameters in high dimensional linear models
Cun-Hui Zhang and Stephanie S Zhang · 2014
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Controlling the false discovery rate via knockoffs
Rina Foygel Barber and Emmanuel J Candès · 2015
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High-dimensional inference: Confidence intervals, p p -values and r-software hdi
Ruben Dezeure, Peter Bühlmann, Lukas Meier, Nicolai Meinshausen, et al · 2015
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Adaptive sequential model selection
William Fithian, Jonathan Taylor, Robert Tibshirani, and Ryan Tibshirani · 2015
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Statistical learning and selective inference
Jonathan Taylor and Robert J Tibshirani · 2015
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Selective inference with a randomized response
Xiaoying Tian and Jonathan E Taylor · 2015
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Uniform asymptotic inference and the bootstrap after model selection
Ryan J Tibshirani, Alessandro Rinaldo, Robert Tibshirani, and Larry Wasserman · 2015
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Rank verification for exponential families
Kenneth Hung and William Fithian · 2016
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Exact post-selection inference, with application to the lasso
Jason D Lee, Dennis L Sun, Yuekai Sun, and Jonathan E Taylor · 2016
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Post-selection inference for l1-penalized likelihood models
Jonathan Taylor and Robert Tibshirani · 2016
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Asymptotics of selective inference
Xiaoying Tian and Jonathan Taylor · 2017
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