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Randomized experiments are considered the gold standard for estimating causal effects. However, out of the set of possible randomized assignments, some may be likely to produce poor effect estimates and misleading conclusions. Restricted…

Methodology · Statistics 2025-08-28 Maggie Wang , René F. Kizilcec , Michael Baiocchi

Adaptive sample size re-estimation, early stopping, and trial re-design at interim analyses can reduce expected sample sizes in randomised trials. Cluster randomised trials, in which groups of participants are randomly allocated to…

Methodology · Statistics 2026-03-09 Samuel I. Watson , James Martin

Allocating patients to treatment arms during a trial based on the observed responses accumulated prior to the decision point, and sequential adaptation of this allocation,, could minimize the expected number of failures or maximize total…

Methodology · Statistics 2022-09-01 Zhongying Xu , Andriy I. Bandos , Tianzhou Ma , Lu Tang , Victor B. Talisa , Chung-Chou H. Chang

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

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

Most Bayesian response-adaptive designs unbalance randomization rates towards the most promising arms with the goal of increasing the number of positive treatment outcomes during the study, even though the primary aim of the trial is…

Applications · Statistics 2018-07-02 Steffen Ventz , Matteo Cellamare , Sergio Bacallado , Lorenzo Trippa

Randomized controlled trials (RCTs) frequently utilize covariate-adaptive randomization (CAR) (e.g., stratified block randomization) and commonly suffer from imperfect compliance. This paper studies the identification and inference for the…

Econometrics · Economics 2025-05-02 Federico A. Bugni , Mengsi Gao , Filip Obradovic , Amilcar Velez

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

Bayesian response adaptive clinical trials are currently evaluating experimental therapies for several diseases. Adaptive decisions, such as pre-planned variations of the randomization probabilities, attempt to accelerate the development of…

Methodology · Statistics 2021-05-25 Marta Bonsaglio , Sandra Fortini , Steffen Ventz , Lorenzo Trippa

Restricting randomization in the design of experiments (e.g., using blocking/stratification, pair-wise matching, or rerandomization) can improve the treatment-control balance on important covariates and therefore improve the estimation of…

Econometrics · Economics 2020-11-02 Brian Quistorff , Gentry Johnson

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

Targeted therapies on the basis of genomic aberrations analysis of the tumor have shown promising results in cancer prognosis and treatment. Regardless of tumor type, trials that match patients to targeted therapies for their particular…

Applications · Statistics 2018-04-18 Yanxun Xu , Peter Mueller , Apostolia M Tsimberidou , Donald Berry

Aims: Combinations of treatments can offer additional benefit over the treatments individually. However, trials of these combinations are lower priority than the development of novel therapies, which can restrict funding, timelines and…

Randomized Response (RR) is a protocol designed to collect and analyze categorical data with local differential privacy guarantees. It has been used as a building block of mechanisms deployed by Big tech companies to collect app or web…

Cryptography and Security · Computer Science 2026-01-14 Carlos Antonio Pinzón , Ehab ElSalamouny , Lucas Massot , Alexis Miller , Héber Hwang Arcolezi , Catuscia Palamidessi

Blocking, a special case of rerandomization, is routinely implemented in the design stage of randomized experiments to balance the baseline covariates. This study proposes a regression adjustment method based on the least absolute shrinkage…

Methodology · Statistics 2024-11-15 Ke Zhu , Hanzhong Liu , Yuehan Yang

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

Participants in clinical trials are often viewed as a unique, finite population. Yet, statistical analyses often assume that participants were randomly sampled from a larger population. Under Complete Randomization, Randomization-Based…

Methodology · Statistics 2025-10-09 Jonathan J. Chipman , Oleksandr Sverdlov , Diane Uschner

The determination of the sample size required by a crossover trial typically depends on the specification of one or more variance components. Uncertainty about the value of these parameters at the design stage means that there is often a…

Methodology · Statistics 2018-03-28 Michael Grayling , Adrian Mander , James Wason

Many phase II clinical trials have used survival outcomes as the primary endpoints in recent decades. Suppose the radiotherapy is evaluated in a phase II trial using survival outcomes. In that case, the competing risk issue often arises…

Applications · Statistics 2022-03-15 Jina Park , Wenjing Hu , Ick Hoon Jin , Hao Liu , Yong Zang

Balancing influential covariates is crucial for valid treatment comparisons in clinical studies. While covariate-adaptive randomization is commonly used to achieve balance, its performance can be inadequate when the number of baseline…

Methodology · Statistics 2024-12-30 Ziqing Guo , Yang Liu , Lucy Xia