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This note describes the optimal policy rule, according to the local asymptotic minimax regret criterion, for best arm identification when there are only two treatments. It is shown that the optimal sampling rule is the Neyman allocation,…

Econometrics · Economics 2022-08-29 Karun Adusumilli

We develop a frequentist decision-theoretic framework for selecting the best arm in one-shot, multi-arm randomized controlled trials (RCTs). Our approach characterizes the minimax-regret (MMR) optimal decision rule for any multivariate…

Econometrics · Economics 2025-10-21 Joonhwi Joo

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

The treatment allocation mechanism in a randomized clinical trial can be optimized by maximizing the nonparametric efficiency bound for a specific measure of treatment effect. Optimal treatment allocations which may or may not depend on…

Methodology · Statistics 2025-05-23 Wei Zhang , Zhiwei Zhang , Aiyi Liu

Multi-armed bandit problems (MABPs) are a special type of optimal control problem well suited to model resource allocation under uncertainty in a wide variety of contexts. Since the first publication of the optimal solution of the classic…

Methodology · Statistics 2015-07-30 Sofía S. Villar , Jack Bowden , 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,…

Precision medicine is an emerging field that takes into account individual heterogeneity to inform better clinical practice. In clinical trials, the evaluation of treatment effect heterogeneity is an important component, and recently, many…

Methodology · Statistics 2023-02-24 Yuejia Xu , Angela M. Wood , Brian D. M. Tom

Purpose: Two-stage single-arm trial designs are commonly used in phase II oncology to infer treatment effects for a binary primary outcome (e.g., tumour response). It is imperative that such studies be designed, analysed, and reported…

Applications · Statistics 2020-07-09 Michael J. Grayling , Adrian P. Mander

Background: Experimental treatments pass through various stages of development. If a treatment passes through early phase experiments, the investigators may want to assess it in a late phase randomised controlled trial. An efficient way to…

Randomized experiments (often known as "A/B tests") are widely used to evaluate product and service innovations. We study how to allocate limited experimentation resources across M concurrent experiments in an experiment-rich regime.…

Methodology · Statistics 2026-03-19 Fenghua Yang , Dae Woong Ham , Stefanus Jasin

We introduce a new multiple type I error criterion for clinical trials with multiple populations. Such trials are of interest in precision medicine where the goal is to develop treatments that are targeted to specific sub-populations…

Methodology · Statistics 2021-02-05 Werner Brannath , Charlie Hillner , Kornelius Rohmeyer

Multi-arm multi-stage (MAMS) trials have gained popularity, due to their improved efficiency in evaluating multiple treatments. A traditional MAMS trial often decreases the expected sample size of the trial compared to just running a…

Multi-arm multi-stage (MAMS) trials have gained popularity to enhance the efficiency of clinical trials, potentially reducing both duration and costs. This paper focuses on designing MAMS trials where no control treatment exists. This can…

Methodology · Statistics 2025-02-12 Peter Greenstreet , Thomas Jaki , Alun Bedding , Pavel Mozgunov

We propose a multi-metric flexible Bayesian framework to support efficient interim decision-making in multi-arm multi-stage phase II clinical trials. Multi-arm multi-stage phase II studies increase the efficiency of drug development, but…

Applications · Statistics 2023-12-15 Suzanne M. Dufault , Angela M. Crook , Katie Rolfe , Patrick P. J. Phillips

We propose new, optimal methods for analyzing randomized trials, when it is suspected that treatment effects may differ in two predefined subpopulations. Such sub-populations could be defined by a biomarker or risk factor measured at…

Methodology · Statistics 2016-11-26 Michael Rosenblum , Han Liu , and En-Hsu Yen

The sequential multiple assignment randomized trial (SMART) is the gold standard trial design to generate data for the evaluation of multi-stage treatment regimes. As with conventional (single-stage) randomized clinical trials, interim…

Methodology · Statistics 2023-09-13 Cole Manschot , Eric Laber , Marie Davidian

Clinical trials with a hybrid control arm (a control arm constructed from a combination of randomized patients and real-world data on patients receiving usual care in standard clinical practice) have the potential to decrease the cost of…

Methodology · Statistics 2021-08-20 Joanna Harton , Brian Segal , Ronac Mamtani , Nandita Mitra , Rebecca Hubbard

An important objective in the development of targeted therapies is to identify the populations where the treatment under consideration has positive benefit risk balance. We consider pivotal clinical trials, where the efficacy of a treatment…

In the experimental design literature, Neyman allocation refers to the practice of allocating units into treated and control groups, potentially in unequal numbers proportional to their respective standard deviations, with the objective of…

Methodology · Statistics 2026-01-15 Jinglong Zhao

A practical limitation of cluster randomized controlled trials (cRCTs) is that the number of available clusters may be small, resulting in an increased risk of baseline imbalance under simple randomization. Constrained randomization…

Methodology · Statistics 2022-01-19 Yunji Zhou , Elizabeth L. Turner , Ryan A. Simmons , Fan Li