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To solve the obscureness in measurement brought about from the weak ergodicity breaking appeared in anomalous diffusions we have suggested the time-averaged mean squared displacement (MSD) $\bar{\delta^2 (\tau)}_\tau$ with a integral…

Statistical Mechanics · Physics 2015-06-11 Hyun-Joo Kim

Researchers often use linear regression to analyse randomized experiments to improve treatment effect estimation by adjusting for imbalances of covariates in the treatment and control groups. Our work offers a randomization-based inference…

Statistics Theory · Mathematics 2022-07-08 Hanzhong Liu , Yuehan Yang

Simulations of extended quantum systems are typically performed by extrapolating results of a sequence of finite-system-size simulations to the thermodynamic limit. In the quantum Monte Carlo community, twist-averaging was pioneered as an…

Strongly Correlated Electrons · Physics 2022-12-14 Sergei Iskakov , Hanna Terletska , Emanuel Gull

Doubly robust estimators have gained popularity in the field of causal inference due to their ability to provide consistent point estimates when either an outcome or exposure model is correctly specified. However, for nonrandomized…

According to Davey et al. (2011) with a total of 22,453 meta-analyses from the January 2008 Issue of the Cochrane Database of Systematic Reviews, the median number of studies included in each meta-analysis is only three. In other words,…

Methodology · Statistics 2020-02-12 Enxuan Lin , Tiejun Tong , Yong Chen , Yuedong Wang

Meta-analysis is a statistical method used in evidence synthesis for combining, analyzing and summarizing studies that have the same target endpoint and aims to derive a pooled quantitative estimate using fixed and random effects models or…

Methodology · Statistics 2022-04-25 Ivette Raices Cruz , Matthias C. M. Troffaes , Johan Lindström , Ullrika Sahlin

We propose a fully data-driven approach to designing mutual information (MI) estimators. Since any MI estimator is a function of the observed sample from two random variables, we parameterize this function with a neural network (MIST) and…

Machine Learning · Computer Science 2026-02-24 German Gritsai , Megan Richards , Maxime Méloux , Kyunghyun Cho , Maxime Peyrard

We study the distribution of hard-, soft-, and adaptive soft-thresholding estimators within a linear regression model where the number of parameters k can depend on sample size n and may diverge with n. In addition to the case of known…

Statistics Theory · Mathematics 2012-01-04 Benedikt M. Pötscher , Ulrike Schneider

When individuals engage in social or physical interactions, a unit's outcome may depend on the treatments received by others. In such interference environments, we provide a unified framework characterizing a broad class of spillover…

Methodology · Statistics 2025-12-16 Fei Fang , Laura Forastiere

Background and Objective: In meta-analysis based on continuous outcome, estimated means and corresponding standard deviations from the selected studies are key inputs to obtain a pooled estimate of the mean and its confidence interval. We…

Computation · Statistics 2020-04-07 Roopesh Reddy Sadashiva Reddy , Isildinha M. Reis , Deukwoo Kwon

In randomized experiments, the actual treatments received by some experimental units may differ from their treatment assignments. This non-compliance issue often occurs in clinical trials, social experiments, and the applications of…

Methodology · Statistics 2022-04-19 Jiyang Ren

We propose a difference-in-differences (DiD) framework with mediation for possibly multivalued discrete or continuous treatments and mediators, aimed at identifying the direct effect of the treatment on the outcome (net of effects operating…

Econometrics · Economics 2026-03-02 Martin Huber , Sarina Joy Oberhänsli

This study addresses the often-overlooked issue of measurability at intermediate points when applying Taylor's theorems to random functions and random vectors (e.g., likelihood functions with respect to estimators) in statistics. Classical…

Other Statistics · Statistics 2025-05-01 Yifan Yang , Xiaoyu Zhou , Ming Wang

We derive new variance formulas for inference on a general class of estimands of causal average treatment effects in a Randomized Control Trial (RCT). We generalize Robins (1988) and show that when the estimand of interest is the Sample…

Statistics Theory · Mathematics 2017-10-19 Jasjeet S. Sekhon , Yotam Shem-Tov

Randomized trials are considered the gold standard for making informed decisions in medicine, yet they often lack generalizability to the patient populations in clinical practice. Observational studies, on the other hand, cover a broader…

Methodology · Statistics 2026-04-14 Piersilvio De Bartolomeis , Javier Abad , Konstantin Donhauser , Fanny Yang

We propose an approach to better inform treatment decisions at an individual level by adapting recent advances in average treatment effect estimation to conditional average treatment effect estimation. Our work is based on doubly robust…

Methodology · Statistics 2023-06-13 Aaron Fisher , Virginia Fisher

In a Phase II dose-finding study with a placebo control, a new drug with several dose levels is compared with a placebo to test for the effectiveness of the new drug. The main focus of such studies often lies in the characterization of the…

Methodology · Statistics 2020-07-14 Saswati Saha , Werner Brannath

Longitudinal studies are often subject to missing data. The ICH E9(R1) addendum addresses the importance of defining a treatment effect estimand with the consideration of intercurrent events. Jump-to-reference (J2R) is one classically…

Methodology · Statistics 2023-12-06 Siyi Liu , Shu Yang , Yilong Zhang , Guanghan , Liu

In this paper we have suggested difference-type estimator for estimation of population mean of the study variable y in the presence of measurement error using auxiliary information. The optimum estimator in the suggested estimator has been…

Statistics Theory · Mathematics 2014-10-02 Viplav Kr. Singh , Rajesh Singh , Florentin Smarandache

Interval analysis, when applied to the so called problem of experimental data fitting, appears to be still in its infancy. Sometimes, partly because of the unrivaled reliability of interval methods, we do not obtain any results at all.…

Data Analysis, Statistics and Probability · Physics 2009-03-03 Marek W. Gutowski