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We propose a restricted win probability estimand for comparing treatments in a randomized trial with a time-to-event outcome. We also propose Bayesian estimators for this summary measure as well as the unrestricted win probability. Bayesian…

Methodology · Statistics 2024-11-06 Michelle Leeberg , Xianghua Luo , Thomas A. Murray

Penalized logistic regression methods are frequently used to investigate the relationship between a binary outcome and a set of explanatory variables. The model performance can be assessed by measures such as the concordance statistic…

Methodology · Statistics 2021-01-20 Angelika Geroldinger , Lara Lusa , Mariana Nold , Georg Heinze

Stepped-wedge cluster randomised trials (SW-CRTs) increasingly evaluate complex interventions, yet methodological guidance for analysing composite endpoints using generalized pairwise comparisons (GPC)remains limited. This work investigates…

This paper presents theoretical results on combining non-probability and probability survey samples through mass imputation, an approach originally proposed by Rivers (2007) as sample matching without rigorous theoretical justification.…

Methodology · Statistics 2020-11-24 Jae Kwang Kim , Seho Park , Yilin Chen , Changbao Wu

We propose a generalized win fraction regression framework for prioritized composite survival outcomes. The framework models the conditional win fraction through a chosen link function (including identity, logit, or probit), thereby…

Methodology · Statistics 2026-04-08 Zhiqiang Cao , Xi Fang , Fan Li

Decision-makers often deploy the best-performing treatment from a randomized experiment, creating a winner's curse: selection favors treatments whose observed outcomes are high partly because of statistical noise, so the na\"ive estimate of…

Econometrics · Economics 2026-05-20 Ron Berman , Walter W. Zhang , Hangcheng Zhao

In the recent COVID-19 pandemic, a wide range of epidemiological modelling approaches have been used to predict the effective reproduction number, R(t), and other COVID-19 related measures such as the daily rate of exponential growth, r(t).…

Applications · Statistics 2021-08-13 T. Maishman , S. Schaap , D. S. Silk , S. J. Nevitt , D. C. Woods , V. E. Bowman

A regression method for proportional, or fractional, data with mixed effects is outlined, designed for analysis of datasets in which the outcomes have substantial weight at the bounds. In such cases a normal approximation is particularly…

Methodology · Statistics 2018-05-23 Colman Humphrey , Dan Swingley

Varying domains and biased datasets can lead to differences between the training and the target distributions, known as covariate shift. Current approaches for alleviating this often rely on estimating the ratio of training and target…

Machine Learning · Statistics 2020-10-27 Bijan Mazaheri , Siddharth Jain , Jehoshua Bruck

In designing external validation studies of clinical prediction models, contemporary sample size calculation methods are based on the frequentist inferential paradigm. One of the widely reported metrics of model performance is net benefit…

Applications · Statistics 2025-02-28 Mohsen Sadatsafavi , Andrew J Vickers , Tae Yoon Lee , Paul Gustafson , Laure Wynants

A method for change point detection is proposed. We consider a univariate sequence of independent random variables with piecewise constant expectation and variance, apart from which the distribution may vary periodically. We aim to detect…

Methodology · Statistics 2021-06-23 Michael Messer

Empirical best prediction (EBP) is a well-known method for producing reliable proportion estimates when the primary data source provides only small or no sample from finite populations. There are potential challenges in implementing…

Methodology · Statistics 2025-01-22 Aditi Sen , Partha Lahiri

Balancing weights have been widely applied to single or monotone missingness due to empirical advantages over likelihood-based methods and inverse probability weighting approaches. This paper considers non-monotone missing data under the…

Methodology · Statistics 2024-12-13 Jianing Dong , Raymond K. W. Wong , Kwun Chuen Gary Chan

This paper proposes confidence regions for the identified set in conditional moment inequality models using Kolmogorov-Smirnov statistics with a truncated inverse variance weighting with increasing truncation points. The new weighting…

Applications · Statistics 2011-12-06 Timothy B. Armstrong

Win statistics have gained increasing popularity as primary analysis methods for clinical trials with hierarchical endpoints (HEs) as primary endpoints. However, existing sample size and power calculation approaches in trial design still…

Methodology · Statistics 2026-05-19 Baoshan Zhang , Huiman X. Barnhart , Yuan Wu , Roland A. Matsouaka

Multi-arm bandit experimental designs are increasingly being adopted over standard randomized trials due to their potential to improve outcomes for study participants, enable faster identification of the best-performing options, and/or…

Methodology · Statistics 2025-06-04 Brian M Cho , Aurélien Bibaut , Nathan Kallus

Stepped wedge cluster randomized trials (SW-CRTs) have become increasingly popular and are used for a variety of interventions and outcomes, often chosen for their feasibility advantages. SW-CRTs must account for time trends in the outcome…

Methodology · Statistics 2024-07-16 Lee Kennedy-Shaffer , Victor De Gruttola , Marc Lipsitch

The properties of the generalized Waring distribution defined on the non negative integers are reviewed. Formulas for its moments and its mode are given. A construction as a mixture of negative binomial distributions is also presented. Then…

Methodology · Statistics 2024-02-29 Louis-Paul Rivest , Mamadou Yauck

Analysis of competing risks data is often complicated by the incomplete or selectively missing information on the cause of failure. Standard approaches typically assume that the cause of failure is missing at random (MAR), an assumption…

Several problems in statistics involve the combination of high-variance unbiased estimators with low-variance estimators that are only unbiased under strong assumptions. A notable example is the estimation of causal effects while combining…

Methodology · Statistics 2023-05-25 Michael Oberst , Alexander D'Amour , Minmin Chen , Yuyan Wang , David Sontag , Steve Yadlowsky