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$P$-values that are derived from continuously distributed test statistics are typically uniformly distributed on $(0,1)$ under least favorable parameter configurations (LFCs) in the null hypothesis. Conservativeness of a $p$-value $P$…

Methodology · Statistics 2023-03-13 Daniel Ochieng , Anh-Tuan Hoang , Thorsten Dickhaus

Combining p-values from multiple independent tests is a fundamental task in statistical inference, but presents unique challenges when the p-values are discrete. We extend a recent optimal transport-based framework for combining discrete…

Methodology · Statistics 2025-08-05 Gonzalo Contador , Zheyang Wu

The randomized $p$-value, (nonrandomized) mid-$p$-value and abstract randomized $p$-value have all been recommended for testing a null hypothesis whenever the test statistic has a discrete distribution. This paper provides a unifying…

Computation · Statistics 2014-12-02 Joshua D Habiger

Many multiple testing procedures make use of the p-values from the individual pairs of hypothesis tests, and are valid if the p-value statistics are independent and uniformly distributed under the null hypotheses. However, it has recently…

Methodology · Statistics 2011-08-25 Joshua D. Habiger , Edsel A. Pena

We are concerned with testing replicability hypotheses for many endpoints simultaneously. This constitutes a multiple test problem with composite null hypotheses. Traditional $p$-values, which are computed under least favourable parameter…

Methodology · Statistics 2020-02-26 Anh-Tuan Hoang , Thorsten Dickhaus

In meta analysis, multiple hypothesis testing and many other methods, p-values are utilized as inputs and assumed to be uniformly distributed over the unit interval under the null hypotheses. If data used to generate p-values have discrete…

Methodology · Statistics 2026-02-24 Joshua Habiger , Pratyaydipta Rudra

Some crucial issues about a recently proposed estimator for the proportion of true null hypotheses ($\pi_0$) under discrete setup are discussed. An estimator for $\pi_0$ is introduced under the same setup. The estimator may be seen as a…

Statistics Theory · Mathematics 2020-09-09 Aniket Biswas , Gaurangadeb Chattopadhyay

Meta-analysis seeks to combine the results of several experiments in order to improve the accuracy of decisions. It is common to use a test for homogeneity to determine if the results of the several experiments are sufficiently similar to…

Methodology · Statistics 2009-08-01 Elena Kulinskaya , Michael B. Dollinger , Kirsten Bjørkestøl

We investigate the multiplicity model with m values of some test statistic independently drawn from a mixture of no effect (null) and positive effect (alternative), where we seek to identify, the alternative test results with a controlled…

Methodology · Statistics 2024-02-06 Zhiwen Jiang , Stephan Morgenthaler

Testing to see whether a given data set comes from some specified distribution is among the oldest types of problems in Statistics. Many such tests have been developed and their performance studied. The general result has been that while a…

Applications · Statistics 2020-12-07 Wolfgang Rolke

We are concerned with multiple test problems with composite null hypotheses and the estimation of the proportion $\pi_{0}$ of true null hypotheses. The Schweder-Spj\o tvoll estimator $\hat{\pi}_0$ utilizes marginal $p$-values and only works…

Methodology · Statistics 2020-04-20 Anh-Tuan Hoang , Thorsten Dickhaus

This paper studies the construction of p-values for nonparametric outlier detection, taking a multiple-testing perspective. The goal is to test whether new independent samples belong to the same distribution as a reference data set or are…

Methodology · Statistics 2024-03-12 Stephen Bates , Emmanuel Candès , Lihua Lei , Yaniv Romano , Matteo Sesia

One class of statistical hypothesis testing procedures is the indisputable equivalence tests, whose main objective is to establish practical equivalence rather than the usual statistical significant difference. These hypothesis tests are…

Methodology · Statistics 2024-01-04 Daniel Ochieng

In this paper, we consider testing the homogeneity of risk differences in independent binomial distributions especially when data are sparse. We point out some drawback of existing tests in either controlling a nominal size or obtaining…

Methodology · Statistics 2018-05-31 Junyong Park , Iris Ivy Gauran

Hypothesis testing plays a central role in statistical inference, and is used in many settings where privacy concerns are paramount. This work answers a basic question about privately testing simple hypotheses: given two distributions $P$…

Data Structures and Algorithms · Computer Science 2019-04-04 Clément L. Canonne , Gautam Kamath , Audra McMillan , Adam Smith , Jonathan Ullman

In the multiple testing context, a challenging problem is the estimation of the proportion $\pi_0$ of true-null hypotheses. A large number of estimators of this quantity rely on identifiability assumptions that either appear to be violated…

Statistics Theory · Mathematics 2008-12-18 Alain Celisse , Stéphane Robin

Equivalence testing is of emerging importance in genomics studies but has hitherto been little studied in this content. In this paper, we define the notion of equivalence of gene expression and determine a `strength of evidence' measure for…

Applications · Statistics 2012-02-03 J. Tuke , G. F. V. Glonek , P. J. Solomon

We investigate the problem of testing the equivalence between two discrete histograms. A {\em $k$-histogram} over $[n]$ is a probability distribution that is piecewise constant over some set of $k$ intervals over $[n]$. Histograms have been…

Data Structures and Algorithms · Computer Science 2017-03-07 Ilias Diakonikolas , Daniel M. Kane , Vladimir Nikishkin

Permutation tests are amongst the most commonly used statistical tools in modern genomic research, a process by which p-values are attached to a test statistic by randomly permuting the sample or gene labels. Yet permutation p-values…

Applications · Statistics 2016-03-21 Belinda Phipson , Gordon K. Smyth

We study the question of identity testing for structured distributions. More precisely, given samples from a {\em structured} distribution $q$ over $[n]$ and an explicit distribution $p$ over $[n]$, we wish to distinguish whether $q=p$…

Data Structures and Algorithms · Computer Science 2014-10-10 Ilias Diakonikolas , Daniel M. Kane , Vladimir Nikishkin
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