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A random access code (RAC) is a communication task in which the sender encodes a random message into a shorter one to be decoded by the receiver so that a randomly chosen character of the original message is recovered with some probability.…

Quantum Physics · Physics 2023-10-23 Gabriel Pereira Alves , Nicolas Gigena , Jędrzej Kaniewski

In conventional randomized controlled trials, adjustment for baseline values of covariates known to be at least moderately associated with the outcome increases the power of the trial. Recent work has shown particular benefit for more…

Methodology · Statistics 2023-11-27 James Willard , Shirin Golchi , Erica EM Moodie

It is common to conduct causal inference in matched observational studies by proceeding as though treatment assignments within matched sets are assigned uniformly at random and using this distribution as the basis for inference. This…

Methodology · Statistics 2023-11-14 Samuel D. Pimentel , Yaxuan Huang

Response-adaptive randomization has recently attracted a lot of attention in the literature. In this paper, we propose a new and simple family of response-adaptive randomization procedures that attain the Cramer--Rao lower bounds on the…

Statistics Theory · Mathematics 2009-08-25 Feifang Hu , Li-Xin Zhang , Xuming He

Individualized treatment rules (ITR) can improve health outcomes by recognizing that patients may respond differently to treatment and assigning therapy with the most desirable predicted outcome for each individual. Flexible and efficient…

Methodology · Statistics 2017-09-25 Brent R. Logan , Rodney Sparapani , Robert E. McCulloch , Purushottam W. Laud

This paper proposes a novel criterion for the allocation of patients in Phase~I dose-escalation clinical trials aiming to find the maximum tolerated dose (MTD). Conventionally, using a model-based approach the next patient is allocated to…

Methodology · Statistics 2018-07-17 Pavel Mozgunov , Thomas Jaki

Bayesian adaptive designs enable flexible clinical trials by adapting features based on accumulating data. Among these, Bayesian Response-Adaptive Randomization (BRAR) skews patient allocation towards more promising treatments based on…

Methodology · Statistics 2025-12-05 Daniel Kaddaj , Stef Baas , Edwin Y. N. Tang , David S. Robertson , Lukas Pin , Sofía S. Villar

In clinical trials, there is potential to improve precision and reduce the required sample size by appropriately adjusting for baseline variables in the statistical analysis. This is called covariate adjustment. Despite recommendations by…

Methodology · Statistics 2022-06-20 Kelly Van Lancker , Joshua Betz , Michael Rosenblum

Randomized experiments are often performed to study the causal effects of interest. Blocking is a technique to precisely estimate the causal effects when the experimental material is not homogeneous. It involves stratifying the available…

Methodology · Statistics 2023-02-21 Abhishek Kumar Umrawal

Covariate-adjusted randomization (CAR) can reduce the risk of covariate imbalance and, when accounted for in analysis, increase the power of a trial. Despite CAR advances, stratified randomization remains the most common CAR method. Matched…

Methodology · Statistics 2023-07-13 Jonathan J. Chipman , Lindsay Mayberry , Robert A. Greevy

Policymakers in resource-constrained settings require experimental designs that satisfy strict budget limits while ensuring precise estimation of treatment effects. We propose a framework that applies a dependent randomized rounding…

Machine Learning · Statistics 2025-06-17 Khurram Yamin , Edward Kennedy , Bryan Wilder

Typically, a randomized experiment is designed to test a hypothesis about the average treatment effect and sometimes hypotheses about treatment effect variation. The results of such a study may then be used to inform policy and practice for…

Methodology · Statistics 2026-05-01 Elizabeth Tipton , Michalis Mamakos

We consider the performance of the difference-in-means estimator in a two-arm randomized experiment under common experimental endpoints such as continuous (regression), incidence, proportion and survival. We examine performance under both…

Statistics Theory · Mathematics 2025-07-08 David Azriel , Abba M. Krieger , Adam Kapelner

Response-adaptive designs allow the randomization probabilities to change during the course of a trial based on cumulated response data, so that a greater proportion of patients can be allocated to the better performing treatments. A major…

Methodology · Statistics 2020-06-03 David S. Robertson , James M. S. Wason

The Regression Discontinuity (RD) design is a quasi-experimental design which emulates a randomised study by exploiting situations where treatment is assigned according to a continuous variable as is common in many drug treatment…

Methodology · Statistics 2016-07-28 Sara Geneletti , Federico Ricciardi , Aidan O'Keeffe , Gianluca Baio

When a novel treatment has successfully passed phase I, different options to design subsequent phase II trials are available. One approach is a single-arm trial, comparing the response rate in the intervention group against a fixed…

Methodology · Statistics 2020-08-03 Johannes Krisam , Dorothea Weber , Richard F. Schlenk , Meinhard Kieser

Random allocation models used in clinical trials aid researchers in determining which of a particular treatment provides the best results by reducing bias between groups. Often however, this determination leaves researchers battling ethical…

Applications · Statistics 2020-08-04 Albert. H. Lee , Edward L Boone , Roy T. Sabo , Erin Donahue

Adaptive designs are commonly used in clinical and drug development studies for optimum utilization of available resources. In this article, we consider the problem of estimating the effect of the selected (better) treatment using a…

Statistics Theory · Mathematics 2023-01-24 Masihuddin , Neeraj Misra

This paper studies the evaluation of methods for targeting the allocation of limited resources to a high-risk subpopulation. We consider a randomized controlled trial to measure the difference in efficiency between two targeting methods and…

Applications · Statistics 2018-04-04 Eric Potash

We consider the problem of how to assign treatment in a randomized experiment, in which the correlation among the outcomes is informed by a network available pre-intervention. Working within the potential outcome causal framework, we…

Methodology · Statistics 2017-05-19 Guillaume W. Basse , Edoardo M. Airoldi