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This paper raises concerns about the advantages of using statistical significance tests in research assessments as has recently been suggested in the debate about proper normalization procedures for citation indicators. Statistical…

Digital Libraries · Computer Science 2012-09-26 Jesper W. Schneider

The score test statistic using the observed information is easy to compute numerically. Its large sample distribution under the null hypothesis is well known and is equivalent to that of the score test based on the expected information, the…

Statistics Theory · Mathematics 2018-08-10 N. Karavarsamis , G. Guillera-Arroita , RM Huggins , B J T Morgan

Empirical researchers often use slope-homogeneity tests to assess whether slopes can be treated as common across units. A key difficulty is that heterogeneity may be concentrated in a small number of units, so that a failure to reject…

Econometrics · Economics 2026-04-16 Antonio Raiola , Nazarii Salish

The test of homogeneity for normal mixtures has been conducted in diverse research areas, but constructing a theory of the test of homogeneity is challenging because the parameter set for the null hypothesis corresponds to singular points…

Statistics Theory · Mathematics 2020-12-02 Natsuki Kariya , Sumio Watanabe

Pearson's chi-square tests are among the most commonly applied statistical tools across a wide range of scientific disciplines, including medicine, engineering, biology, sociology, marketing and business. However, its usage in some areas is…

Methodology · Statistics 2025-05-13 Vladimir Gurvich , Mariya Naumova

A common problem in numerous research areas, particularly in clinical trials, is to test whether the effect of an explanatory variable on an outcome variable is equivalent across different groups. In practice, these tests are frequently…

Methodology · Statistics 2024-05-03 Niklas Hagemann , Kathrin Möllenhoff

We propose a general and formal statistical framework for multiple tests of association between known fixed features of a genome and unknown parameters of the distribution of variable features of this genome in a population of interest. The…

Applications · Statistics 2008-12-18 Sandrine Dudoit , Sündüz Keleş , Mark J. van der Laan

We propose a general, modular method for significance testing of groups (or clusters) of variables in a high-dimensional linear model. In presence of high correlations among the covariables, due to serious problems of identifiability, it is…

Statistics Theory · Mathematics 2015-02-12 Jacopo Mandozzi , Peter Bühlmann

In this article, we consider the problem of simultaneous testing of hypotheses when the individual test statistics are not necessarily independent. Specifically, we consider the problem of simultaneous testing of point null hypotheses…

Statistics Theory · Mathematics 2018-07-17 Prasenjit Ghosh , Arijit Chakrabarti

We propose a non-parametric, two-sample Bayesian test for checking whether or not two data sets share a common distribution. The test makes use of data splitting ideas and does not require priors for high-dimensional parameter vectors as do…

Methodology · Statistics 2020-03-16 Jeffery Hart , Taeryon Choi , Naveed Merchant

We construct a procedure to test the stochastic order of two samples of interval-valued data. We propose a test statistic which belongs to U-statistic and derive its asymptotic distribution under the null hypothesis. We compare the…

Methodology · Statistics 2019-12-05 Hyejeong Choi , Johan Lim , Minjung Kwak , Seongoh Park

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly…

We say that an ideal I is homogeneous, if its restriction to any I-positive subset is isomorphic to I. The paper investigates basic properties of this notion -- we give examples of homogeneous ideals and present some applications to…

Logic · Mathematics 2017-09-26 Adam Kwela , Jacek Tryba

In observational studies of discrimination, the most common statistical approaches consider either the rate at which decisions are made (benchmark tests) or the success rate of those decisions (outcome tests). Both tests, however, have…

Applications · Statistics 2025-03-07 Johann D. Gaebler , Sharad Goel

The complicated, evolving landscape of cancer mutations poses a formidable challenge to identify cancer genes among the large lists of mutations typically generated in NGS experiments. The ability to prioritize these variants is therefore…

Gene Set Enrichment Analysis (GSEA) is a basic tool for genomic data treatment. From a statistical point of view, the centering of its test statistic does not allow the derivation of asymptotic results. A test statistic with a different…

Probability · Mathematics 2014-10-08 Konstantina Charmpi , Bernard Ycart

We propose a general methodology for testing whether a given polynomial with integer coefficients is identically zero. The methodology evaluates the polynomial at efficiently computable approximations of suitable irrational points. In…

Data Structures and Algorithms · Computer Science 2007-05-23 Zhi-Zhong Chen , Ming-Yang Kao

We investigate the signatures of the recently proposed Higgsless models at future colliders. We focus on tests of the mechanism of partial unitarity restoration in the longitudinal vector boson scattering, which do not depend on any…

High Energy Physics - Phenomenology · Physics 2009-10-09 Andreas Birkedal , Konstantin T. Matchev , Maxim Perelstein

We are interested in testing general linear hypotheses in a high-dimensional multivariate linear regression model. The framework includes many well-studied problems such as two-sample tests for equality of population means, MANOVA and…

Methodology · Statistics 2018-10-05 Haoran Li , Alexander Aue , Debashis Paul

The lack of non-parametric statistical tests for confounding bias significantly hampers the development of robust, valid and generalizable predictive models in many fields of research. Here I propose the partial and full confounder tests,…

Machine Learning · Computer Science 2025-05-30 Tamas Spisak
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