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Multistage design has been used in a wide range of scientific fields. By allocating sensing resources adaptively, one can effectively eliminate null locations and localize signals with a smaller study budget. We formulate a…

Methodology · Statistics 2024-06-17 Weinan Wang , Bowen Gang , Wenguang Sun

Random testing (RT) is a well-studied testing method that has been widely applied to the testing of many applications, including embedded software systems, SQL database systems, and Android applications. Adaptive random testing (ART) aims…

Software Engineering · Computer Science 2020-07-15 Rubing Huang , Weifeng Sun , Yinyin Xu , Haibo Chen , Dave Towey , Xin Xia

The majority of response-adaptive randomisation (RAR) designs in the literature rely on efficacy data to guide dynamic patient allocation. However, their applicability becomes limited in settings where efficacy outcomes, such as survival,…

Methodology · Statistics 2026-02-23 Maria Vittoria Chiaruttini , Lukas Pin , Sofia S. Villar

A dynamic treatment regimen (DTR) is a pre-specified sequence of decision rules which maps baseline or time-varying measurements on an individual to a recommended intervention or set of interventions. Sequential multiple assignment…

Methodology · Statistics 2019-10-23 Brook Luers , Min Qian , Inbal Nahum-Shani , Connie Kasari , Daniel Almirall

Sequential multiple assignment randomized trials (SMARTs) are used to construct data-driven optimal intervention strategies for subjects based on their intervention and covariate histories in different branches of health and behavioral…

Methodology · Statistics 2022-04-28 Palash Ghosh , Xiaoxi Yan , Bibhas Chakraborty

The treatment assignment mechanism in a randomized clinical trial can be optimized for statistical efficiency within a specified class of randomization mechanisms. Optimal designs of this type have been characterized in terms of the…

Methodology · Statistics 2025-09-03 Wei Zhang , Zhiwei Zhang , Aiyi Liu

Randomized experiments have been the gold standard for assessing the effectiveness of a treatment or policy. The classical complete randomization approach assigns treatments based on a prespecified probability and may lead to inefficient…

Methodology · Statistics 2023-10-26 Waverly Wei , Xinwei Ma , Jingshen Wang

Randomized Controlled Trials (RCTs) are the gold standard for comparing the effectiveness of a new treatment to the current one (the control). Most RCTs allocate the patients to the treatment group and the control group by uniform…

Machine Learning · Statistics 2018-10-22 Onur Atan , William R. Zame , Mihaela van der Schaar

Response adaptive randomization (RAR) is appealing from methodological, ethical, and pragmatic perspectives in the sense that subjects are more likely to be randomized to better performing treatment groups based on accumulating data.…

Methodology · Statistics 2022-08-03 Tianyu Zhan , Lu Cui , Ziqian Geng , Lanju Zhang , Yihua Gu , Ivan S. F. Chan

Maximizing statistical power in experimental design often involves imbalanced treatment allocation, but several challenges hinder its practical adoption: (1) the misconception that equal allocation always maximizes power, (2) when only…

Methodology · Statistics 2025-09-17 Stef Baas , Lukas Pin , Sofía S. Villar , William F. Rosenberger

Response-Adaptive Randomization (RAR) is recognized for its potential to deliver improvements in patient benefit. However, the utility of RAR is contingent on regularization methods to mitigate early instability and preserve statistical…

Methodology · Statistics 2025-11-27 Lukas Pin , Stef Baas , Gianmarco Caruso , David S. Robertson , Sofía S. Villar

Response-adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates.…

Applications · Statistics 2017-03-14 Sofia S. Villar , Jack Bowden , James Wason

Clinical trials are complex and usually involve multiple objectives such as controlling type I error rate, increasing power to detect treatment difference, assigning more patients to better treatment, and more. In literature, both…

Statistics Theory · Mathematics 2010-10-20 Hongjian Zhu , Feifang Hu

Background: Missing data poses an acute threat to sequential multiple assignment randomized trial (SMART) analyses because of the sequential treatment structure and response-dependent re-randomization. Objectives: This study aimed to (1)…

Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each stage by potentially time-varying patient features and intermediate outcomes observed in previous stages. The complexity, patient heterogeneity and chronicity…

Methodology · Statistics 2016-11-09 Ying Liu , Yuanjia Wang , Michael R. Kosorok , Yingqi Zhao , Donglin Zeng

Randomized controlled trials typically assume that prognostic covariates are known and available at no cost. In practice, obtaining high-dimensional pretreatment data is costly, forcing a trade-off between covariate-adaptive precision and a…

Machine Learning · Statistics 2026-05-08 Kateryna Husar , Alexander Volfovsky

One of the main goals of sequential, multiple assignment, randomized trials (SMART) is to find the most efficacious design embedded dynamic treatment regimes. The analysis method known as multiple comparisons with the best (MCB) allows…

Methodology · Statistics 2020-08-07 William J. Artman , Ashkan Ertefaie , Kevin G. Lynch , James R. McKay

Sequential multiple assignment randomized trials (SMARTs) provide a systematic framework for constructing and evaluating dynamic treatment regimens (DTRs). In clinical studies, longitudinal biomarkers are routinely collected to monitor…

Methodology · Statistics 2026-05-06 Zhengxi Chen , Holly Hartman

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

Traditional randomized A/B experiments assign arms with uniform random (UR) probability, such as 50/50 assignment to two versions of a website to discover whether one version engages users more. To more quickly and automatically use data to…