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Most of the popular dependence measures for two random variables $X$ and $Y$ (such as Pearson's and Spearman's correlation, Kendall's $\tau$ and Gini's $\gamma$) vanish whenever $X$ and $Y$ are independent. However, neither does a vanishing…

Statistics Theory · Mathematics 2023-02-28 Christopher Strothmann , Holger Dette , Karl Friedrich Siburg

Covariate balance is crucial for unconfounded descriptive or causal comparisons. However, lack of balance is common in observational studies. This article considers weighting strategies for balancing covariates. We define a general class of…

Methodology · Statistics 2016-09-30 Fan Li , Kari Lock Morgan , Alan M. Zaslavsky

Covariate balance is crucial for unconfounded descriptive or causal comparisons. However, lack of balance is common in observational studies. This article considers weighting strategies for balancing covariates. We define a general class of…

Methodology · Statistics 2016-11-17 Fan Li , Kari Lock Morgan , Alan M. Zaslavsky

A new approach based on censoring and moment criterion is introduced for parameter estimation of count distributions when the probability generating function is available even though a closed form of the probability mass function and/or…

Statistics Theory · Mathematics 2024-09-18 Antonio Di Noia , Marzia Marcheselli , Caterina Pisani , Luca Pratelli

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,…

Kendall transformation is a conversion of an ordered feature into a vector of pairwise order relations between individual values. This way, it preserves ranking of observations and represents it in a categorical form. Such transformation…

Machine Learning · Computer Science 2023-08-15 Miron Bartosz Kursa

This paper considers estimation and inference about tail features when the observations beyond some threshold are censored. We first show that ignoring such tail censoring could lead to substantial bias and size distortion, even if the…

Econometrics · Economics 2020-02-25 Yulong Wang , Zhijie Xiao

This paper describes our approach for the triple scoring task at the WSDM Cup 2017. The task required participants to assign a relevance score for each pair of entities and their types in a knowledge base in order to enhance the ranking…

Computation and Language · Computer Science 2017-04-06 Ikuya Yamada , Motoki Sato , Hiroyuki Shindo

In this paper we consider a group sequentially monitored trial on a survival endpoint, monitored using a weighted log-rank (WLR) statistic with deterministic weight function. We introduce a summary statistic in the form of a weighted…

Methodology · Statistics 2017-11-30 Grant Izmirlian

Recently, weighted cumulative residual Tsallis entropy has been introduced in the literature as a generalization of weighted cumulative residual entropy. We study some new properties of weighted cumulative residual Tsallis entropy measure.…

Statistics Theory · Mathematics 2026-02-02 Siddhartha Chakraborty , Asok K. Nanda

Methods for random-effects meta-analysis require an estimate of the between-study variance, $\tau^2$. The performance of estimators of $\tau^2$ (measured by bias and coverage) affects their usefulness in assessing heterogeneity of…

Methodology · Statistics 2019-04-04 Ilyas Bakbergenuly , David C. Hoaglin , Elena Kulinskaya

We propose an empirically stable and asymptotically efficient covariate-balancing approach to the problem of estimating survival causal effects in data with conditionally-independent censoring. This addresses a challenge often encountered…

The instability in the selection of models is a major concern with data sets containing a large number of covariates. This paper deals with variable selection methodology in the case of high-dimensional problems where the response variable…

Applications · Statistics 2012-03-23 Marie Walschaerts , Eve Leconte , Philippe Besse

Considering censored outcomes in survival analysis can lead to quite complex results in the model setting of causal inference. Causal inference has attracted a lot of attention over the past few years, but little research has been done on…

Methodology · Statistics 2025-09-11 Byeonghee Lee , Joonsung Kang

This paper discusses estimation and limited information goodness-of-fit test statistics in factor models for binary data using pairwise likelihood estimation and sampling weights. The paper extends the applicability of pairwise likelihood…

Methodology · Statistics 2026-03-30 Haziq Jamil , Irini Moustaki , Chris Skinner

Two-sample tests with censored outcomes are a classical topic in statistics with wide use even in cutting edge applications. There are at least two modes of inference used to justify two-sample tests. One is usual superpopulation inference…

Statistics Theory · Mathematics 2022-10-06 Xinran Li , Dylan S. Small

Interval-censored competing risks data arise when each study subject may experience an event or failure from one of several causes and the failure time is not observed exactly but rather known to lie in an interval between two successive…

Methodology · Statistics 2016-03-02 Lu Mao , D. Y. Lin , Donglin Zeng

We present a conformal inference method for constructing lower prediction bounds for survival times from right-censored data, extending recent approaches designed for more restrictive type-I censoring scenarios. The proposed method imputes…

Methodology · Statistics 2025-05-26 Matteo Sesia , Vladimir Svetnik

We propose a class of two-sample statistics for testing the equality of proportions and the equality of survival functions. We build our proposal on a weighted combination of a score test for the difference in proportions and a Weighted…

Methodology · Statistics 2021-12-08 Marta Bofill Roig , Guadalupe Gómez Melis

Estimating the causal effect of a treatment or health policy with observational data can be challenging due to an imbalance of and a lack of overlap between treated and control covariate distributions. In the presence of limited overlap,…

Methodology · Statistics 2025-03-24 Martha Barnard , Jared D. Huling , Julian Wolfson