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相关论文: A new composite Mann-Whitney test for two-sample s…

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The Mann-Whitney effect is an intuitive measure for discriminating two survival distributions. Here we analyze various inference techniques for this parameter in a two-sample survival setting with independent right-censoring, where the…

统计理论 · 数学 2016-09-26 Dennis Dobler , Markus Pauly

Given independent samples from two univariate distributions, the one-sided Wilcoxon-Mann-Whitney statistic may be used to conduct a rank-based test of first-order stochastic dominance. We broaden the scope of applicability of such tests by…

计量经济学 · 经济学 2026-03-03 Brendan K. Beare , Jackson D. Clarke

We develop a new rank-based approach for univariate two-sample testing in the presence of missing data which makes no assumptions about the missingness mechanism. This approach is a theoretical extension of the Wilcoxon-Mann-Whitney test…

统计方法学 · 统计学 2024-03-25 Yijin Zeng , Niall M. Adams , Dean A. Bodenham

In scientific research, many hypotheses relate to the comparison of two independent groups. Usually, it is of interest to use a design (i.e., the allocation of sample sizes $m$ and $n$ for fixed $N = m + n$) that maximizes the power of the…

统计方法学 · 统计学 2022-11-24 Paul-Christian Bürkner , Philipp Doebler , Heinz Holling

The Wilcoxon signed-rank test and the Wilcoxon-Mann-Whitney test are commonly employed in one sample and two sample mean tests for one-dimensional hypothesis problems. For high-dimensional mean test problems, we calculate the asymptotic…

统计方法学 · 统计学 2024-01-02 Yu Zhang , Long Feng

Randomly censored survival data are frequently encountered in applied sciences including biomedical or reliability applications and clinical trial analyses. Testing the significance of statistical hypotheses is crucial in such analyses to…

统计方法学 · 统计学 2019-01-08 Abhik Ghosh , Ayanendranath Basu , Leandro Pardo

There are many different proposed procedures for sample size planning for the Wilcoxon-Mann-Whitney test at given type-I and type-II error rates $\alpha$ and $\beta$, respectively. Most methods assume very specific models or types of data…

统计方法学 · 统计学 2018-10-10 Martin Happ , Arne C. Bathke , Edgar Brunner

Studies to compare the survival of two or more groups using time-to-event data are of high importance in medical research. The gold standard is the log-rank test, which is optimal under proportional hazards. As the latter is no simple…

统计方法学 · 统计学 2022-10-25 Ina Dormuth , Tiantian Liu , Jin Xu , Markus Pauly , Marc Ditzhaus

So-called linear rank statistics provide a means for distribution-free (even in finite samples), yet highly flexible, two-sample testing in the setting of univariate random variables. Their flexibility derives from a choice of weights that…

统计方法学 · 统计学 2023-10-03 Dan D. Erdmann-Pham

This paper proposes a new statistical test to assess the dominance of survival functions in the presence of right-censored data. Traditional methods, such as the log-rank test, are inadequate for determining whether one survival function…

统计方法学 · 统计学 2025-04-10 Félix Belzunce , Carolina Martínez-Riquelme , Jaime Valenciano

The parametric Welch $t$-test and the non-parametric Wilcoxon-Mann-Whitney test are the most commonly used two independent sample means tests. More recent testing approaches include the non-parametric, empirical likelihood and exponential…

统计方法学 · 统计学 2019-10-08 Michail Tsagris , Abdulaziz Alenazi , Kleio-Maria Verrou , Nikolaos Pandis

The Mann-Whitney-Wilcoxon rank sum test (MWWRST) is a widely used method for comparing two treatment groups in randomized control trials, particularly when dealing with highly skewed data. However, when applied to observational study data,…

This paper introduces new effect parameters for factorial survival designs with possibly right-censored time-to-event data. In the special case of a two-sample design it coincides with the concordance or Wilcoxon parameter in survival…

统计理论 · 数学 2018-07-30 Dennis Dobler , Markus Pauly

Nonparametric tests for functional data are a challenging class of tests to work with because of the potentially high dimensional nature of the data. One of the main challenges for considering rank-based tests, like the Mann-Whitney or…

统计方法学 · 统计学 2024-07-12 Mark J. Meyer

The log-normal distribution is one of the most common distributions used for modeling skewed and positive data. It frequently arises in many disciplines of science, specially in the biological and medical sciences. The statistical analysis…

统计方法学 · 统计学 2020-01-01 Ayanendranath Basu , Abhijit Mandal , Nirian Martin , Leandro Pardo

We develop a systematic, omnibus approach to goodness-of-fit testing for parametric distributional models when the variable of interest is only partially observed due to censoring and/or truncation. In many such designs, tests based on the…

统计方法学 · 统计学 2026-02-10 Juan Carlos Escanciano , Jacobo de Uña-Álvarez

The Wilcoxon-Mann-Whitney test is a robust competitor of the t-test in the univariate setting. For finite dimensional multivariate data, several extensions of the Wilcoxon-Mann-Whitney test have been shown to have better performance than…

统计方法学 · 统计学 2014-03-04 Anirvan Chakraborty , Probal Chaudhuri

We propose a method for comparing survival data based on the higher criticism of p-values obtained from multiple exact hypergeometric tests. The method accommodates non-informative right-censorship and is sensitive to hazard differences in…

统计理论 · 数学 2025-10-28 Alon Kipnis , Ben Galili , Zohar Yakhini

Nonparametric two sample testing deals with the question of consistently deciding if two distributions are different, given samples from both, without making any parametric assumptions about the form of the distributions. The current…

统计理论 · 数学 2014-11-25 Aaditya Ramdas , Sashank J. Reddi , Barnabas Poczos , Aarti Singh , Larry Wasserman

The Mann-Whitney effect is an effect measure for the order of two sample-specific outcome variables. It has the interpretation of a probability and also a connection to the area under the ROC curve. In the literature it has been considered…

统计方法学 · 统计学 2026-04-02 Dennis Dobler , Alina Schenk , Matthias Schmid
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