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Contributed Papers

New developments in hypothesis testing

Tue, Aug 5, 2:00 PM - 3:50 PM Room CC-101C Music City Center

Jacqueline JohnsonChair

IMS

6 Presentations

A unifying framework for selective inference with applications in rank verification

2:05 PM - 2:20 PM

Co-authors: Anav Sood (Stanford University), Anav Sood (Stanford University)

Selective inference Winner's curse Rank Verification Publication bias Data carving Conditional inference

Aggregating Dependent Signals with Heavy-Tailed Combination Tests

2:20 PM - 2:35 PM

Co-authors: Lin Gui, Tiantian Mao (The University of Science and Technology of China), Yuchao Jiang (Texas A&M University), Lin Gui, Jingshu Wang, Ruodu Wang (University of Waterloo)

Cauchy combination test Dependent p-values combination Quasi-asymptotic independence t-copula

Approximation methods for global hypothesis testing with discrete and non independent p-values

2:35 PM - 2:50 PM

Co-authors: Gonzalo Contador, Gonzalo Contador

Global hypotesis testing Approximation Theory Cauchy Combination Statistic Discrete and dependent p-values Wasserstein Metric Case-control studies

Boosting e-BH via conditional calibration

2:50 PM - 3:05 PM

Co-authors: Junu Lee (University of Pennsylvania), Junu Lee (University of Pennsylvania), Zhimei Ren

e-values multiple testing variable selection conformal inference novelty detection model-X knockoffs

Testing multivariate normality using angular skewness and kurtosis processes

3:05 PM - 3:20 PM

Co-authors: Jisu Oh (North Carolina State University), Subhashis Ghoshal (North Carolina State University), Jisu Oh (North Carolina State University)

multivariate normality test skewness and kurtosis stochastic processes spherical harmonics emprical processes Bayesian bootstrap

Testing Random Effects for Binomial Data: Minimax Goodness-of-Fit Testing and Meta-analyses

3:20 PM - 3:35 PM

Co-authors: Lucas Kania (Carnegie Mellon University), Sivaraman Balakrishnan (Carnegie Mellon University), Lucas Kania (Carnegie Mellon University), Larry Wasserman (Carnegie Mellon University)

hypothesis testing meta-analysis local minimax critical separation Wasserstein distance homogeneity testing

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