Exact and Approximate Stepdown Methods for Multiple Hypothesis Testing

By Joseph P. Romano, Michael Wolf. 2005

592 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/79ee6103a4a8efa556693810d513216ba0a9cc7c

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In Aerospace Engineering

In Statistics and Probability

Citations in the corpus

Intergenerational and Intragenerational Externalities of the Perry Preschool Project (2019, unknown): “In the appendix, we also report adjusted p-values based on multiple hypothesis tests developed by Holm (1979) and Romano and Wolf (2005).”
On the uniform asymptotic validity of subsampling and the bootstrap (2012, background): “nds to zero uniformly in x. But this follows by simply absorbing the terms (1 − δ) √ nµj(Pn) σj(Pn) into the x and arguing as in the proof of Theorem 3.1. 35 4.11 Proofof Theorem 3.4 By arguing as in Romano and Wolf (2005), we see that FWERP ≤ P ˆ max j∈K0(P) √ nX¯ j,n Sj,n > L−1 n (1 −α,K0(P)) ˙”
Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results* (2018, background): “…require either “subset pivotality” (Westfall & Young 1993), i.e. that the multivariate distribution of p-values for subsets of hypotheses does not depend upon the truth of other hypotheses, or, more generally, that critical values are weakly monotonic in subsets of hypotheses (Romano & Wolf 2005).”
EARLY CHILDHOOD INVESTMENTS SUBSTANTIALLY BOOST ADULT HEALTH (2014, methodology): “We account for the multiplicity of the hypotheses being tested using recently developed stepdown procedures (24).”
TESTING REGRESSION MONOTONICITY IN ECONOMETRIC MODELS (2012, methodology): “It is somewhat related to methods developed in Romano and Wolf (2005a) and Romano and Shaikh (2010) but the details are rather different.”
Hypothesis Testing in Econometrics (2010, methodology): “See Romano and Wolf (2005, 2007) for details.”
Minimax optimality of permutation tests (2020, methodology): “Therefore it is common practice to use Monte-Carlo simulations to approximate the critical value (e.g. Romano and Wolf, 2005).”
Control of generalized error rates in multiple testing (2007, methodology): “1 of [28] in the case k = 1; an analogous construction works for general k.”
Efficient computation of adjusted p-values for resampling-based stepdown multiple testing (2016, methodology): “Details for the bootstrap method can be found in Romano and Wolf (2005a, Section 4.2), Romano and Wolf (2005b), and Romano et al. (2008, Section 4.3).”
Asymptotic optimality of the Westfall--Young permutation procedure for multiple testing under dependence (2011, methodology): “Romano and Wolf [29] refer to this as the “randomization hypothesis.””
Estimating Marginal Returns to Education (2010, unknown): “9”
Confidence sets for model selection by F -testing (2015, methodology): “Their approach is analogous to some step-down procedures for multiple hypothesis testing (e.g., Dudoit et al. (2003), Lehmann and Romano (2006), Ch. 9, or Romano and Wolf (2005)), as is mentioned in Hansen et al. (2011).”
Simultaneous Inference for High-Dimensional Linear Models (2016, methodology): “…3.2 and 3.3, this test statistic can be naturally coupled with the margin screening (Fan and Lv 2008) to enhance its power in sparse testing and also reduce the computational cost in nodewise Lasso, or with the step-down method (Romano and Wolf 2005) to provide a strong control for the FWER.”
Balanced Control of Generalized Error Rates (2010, background): “set of all bootstrap samples from the original data.) To see how this is done in the case k = 1; see Romano and Wolf (2005) .”