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Clinical trials are an instrument for making informed decisions based on evidence from well-designed experiments. Here we consider adaptive designs mainly from the perspective of multi-arm Phase II clinical trials, in which one or more…

Methodology · Statistics 2021-08-31 Elja Arjas , Dario Gasbarra

Practitioners conducting adaptive experiments often encounter two competing priorities: maximizing total welfare (or `reward') through effective treatment assignment and swiftly concluding experiments to implement population-wide…

Machine Learning · Computer Science 2024-07-31 Chao Qin , Daniel Russo

The question of selecting the "best" amongst different choices is a common problem in statistics. In drug development, our motivating setting, the question becomes, for example: what is the dose that gives me a pre-specified risk of…

Statistics Theory · Mathematics 2018-03-15 Pavel Mozgunov , Thomas Jaki

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

Adaptive experiments are used extensively in online platforms, healthcare and biotechnology, and a variety of other settings. In many of these applications, the main goal is not to precisely estimate a treatment effect, but to demonstrate…

Statistics Theory · Mathematics 2026-03-10 Guido Imbens , Lorenzo Masoero , Alexander Rakhlin , Thomas S. Richardson , Suhas Vijaykumar

Response-adaptive clinical trial designs allow targeting a given objective by skewing the allocation of participants to treatments based on observed outcomes. Response-adaptive designs face greater regulatory scrutiny due to potential type…

Methodology · Statistics 2025-03-19 Stef Baas , Peter Jacko , Sofía S. Villar

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

Background: Advanced adaptive randomised clinical trials are increasingly used. Compared to their conventional counterparts, their flexibility may make them more efficient, increase the probability of obtaining conclusive results without…

Testing whether a variable of interest affects the outcome is one of the most fundamental problem in statistics and is often the main scientific question of interest. To tackle this problem, the conditional randomization test (CRT) is…

Methodology · Statistics 2023-05-26 Dae Woong Ham , Jiaze Qiu

This paper considers the optimal adaptive allocation of measurement effort for identifying the best among a finite set of options or designs. An experimenter sequentially chooses designs to measure and observes noisy signals of their…

Machine Learning · Computer Science 2018-06-11 Daniel Russo

Multi-arm trials are gaining interest in practice given the statistical and logistical advantages they can offer. The standard approach uses a fixed allocation ratio, but there is a call for making it adaptive and skewing the allocation of…

Methodology · Statistics 2026-01-16 Gianmarco Caruso , Pavel Mozgunov

Minimizing the number of patients exposed to potentially harmful drugs in early onco logical trials is a major concern during planning. Adaptive designs account for the inherent uncertainty about the true effect size by determining the…

Applications · Statistics 2016-05-03 Kevin Kunzmann , Meinhard Kieser

Platform trials are randomized clinical trials that allow simultaneous comparison of multiple interventions, usually against a common control. Arms to test experimental interventions may enter and leave the platform over time. This implies…

Methodology · Statistics 2024-04-12 Marta Bofill Roig , Ekkehard Glimm , Tobias Mielke , Martin Posch

Adaptive experiments such as multi-arm bandits adapt the treatment-allocation policy and/or the decision to stop the experiment to the data observed so far. This has the potential to improve outcomes for study participants within the…

Methodology · Statistics 2024-05-03 Aurélien Bibaut , Nathan Kallus

We study the problem of best-arm identification with fixed budget in stochastic multi-armed bandits with Bernoulli rewards. For the problem with two arms, also known as the A/B testing problem, we prove that there is no algorithm that (i)…

Machine Learning · Statistics 2024-06-05 Po-An Wang , Kaito Ariu , Alexandre Proutiere

Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of, stepped-wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of…

Methodology · Statistics 2018-06-29 Michael Grayling , Adrian Mander , James Wason

Background: trials to identify the minimal effective treatment duration are needed in different therapeutic areas, including bacterial infections, TB and Hepatitis--C. However, standard non-inferiority designs have several limitations,…

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

The standard paradigm for confirmatory clinical trials is to compare experimental treatments with a control, for example the standard of care or a placebo. However, it is not always the case that a suitable control exists. Efficient…

Methodology · Statistics 2024-10-29 Thomas Burnett , Thomas Jaki

Sampling from distributions to find the one with the largest mean arises in a broad range of applications, and it can be mathematically modeled as a multi-armed bandit problem in which each distribution is associated with an arm. This paper…

Machine Learning · Statistics 2013-06-18 Kevin Jamieson , Matthew Malloy , Robert Nowak , Sebastien Bubeck
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