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The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19.…

Clinical trials are an integral component of medical research. Trials require careful design to, for example, maintain the safety of participants, use resources efficiently and allow clinically meaningful conclusions to be drawn. Adaptive…

Methodology · Statistics 2025-07-17 James M. McGree , Antony M. Overstall , Mark Jones , Robert K. Mahar

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

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

In developing products for rare diseases, statistical challenges arise due to the limited number of patients available for participation in drug trials and other clinical research. Bayesian adaptive clinical trial designs offer the…

Applications · Statistics 2019-09-19 Xiao Wu , Yi Xu , Bradley P. Carlin

An early phase clinical trial is the first step in evaluating the effects in humans of a potential new anti-disease agent or combination of agents. Usually called "phase I" or "phase I/II" trials, these experiments typically have the…

Methodology · Statistics 2010-12-01 Peter F. Thall

The construction of decision-theoretic Bayesian designs for realistically-complex nonlinear models is computationally challenging, as it requires the optimization of analytically intractable expected utility functions over high-dimensional…

Methodology · Statistics 2016-07-01 Antony Overstall , David Woods

Platform trials evaluate multiple experimental treatments against a common control group (and/or against each other), which often reduces the trial duration and sample size. Bayesian platform designs offer several practical advantages,…

Methodology · Statistics 2025-07-18 Luke Hagar , Lara Maleyeff , Shirin Golchi , Dick Menzies

Adaptive approaches, allowing for more flexible trial design, have been proposed for individually randomized trials to save time or reduce sample size. However, adaptive designs for cluster-randomized trials in which groups of participants…

Methodology · Statistics 2022-01-10 Junwei Shen , Shirin Golchi , Erica E. M. Moodie , David Benrimoh

Clinical trials usually involve sequential patient entry. When designing a clinical trial, it is often desirable to include a provision for interim analyses of accumulating data with the potential for stopping the trial early. We review…

Methodology · Statistics 2023-03-13 Tianjian Zhou , Yuan Ji

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

The process of calibrating computer models of natural phenomena is essential for applications in the physical sciences, where plenty of domain knowledge can be embedded into simulations and then calibrated against real observations. Current…

Machine Learning · Computer Science 2025-01-20 Rafael Oliveira , Dino Sejdinovic , David Howard , Edwin V. Bonilla

Bayesian inference and the use of posterior or posterior predictive probabilities for decision making have become increasingly popular in clinical trials. The current practice in Bayesian clinical trials relies on a hybrid…

Methodology · Statistics 2024-04-30 Shirin Golchi , James Willard

Adaptive designs for clinical trials permit alterations to a study in response to accumulating data in order to make trials more flexible, ethical and efficient. These benefits are achieved while preserving the integrity and validity of the…

Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain. Recent developments in deep neural networks and normalizing flows…

Quantum Physics · Physics 2023-06-27 Leopoldo Sarra , Florian Marquardt

Bayesian optimal design is considered for experiments where the response distribution depends on the solution to a system of non-linear ordinary differential equations. The motivation is an experiment to estimate parameters in the equations…

Methodology · Statistics 2019-05-02 Antony Overstall , David Woods , Ben Parker

A new approach to adaptive design of clinical trials is proposed in a general multiparameter exponential family setting, based on generalized likelihood ratio statistics and optimal sequential testing theory. These designs are easy to…

Statistics Theory · Mathematics 2011-05-25 Jay Bartroff , Tze Leung Lai

Interval designs are a class of phase I trial designs for which the decision of dose assignment is determined by comparing the observed toxicity rate at the current dose with a prespecified (toxicity tolerance) interval. If the observed…

Methodology · Statistics 2013-09-20 Suyu Liu , Ying Yuan

Design of experiments has traditionally relied on the frequentist hypothesis testing framework where the optimal size of the experiment is specified as the minimum sample size that guarantees a required level of power. Sample size…

Methodology · Statistics 2025-08-07 Shirin Golchi , Luke Hagar

In the design of clinical trials, it is essential to assess the design operating characteristics (e.g., power and the type I error rate). Common practice for the evaluation of operating characteristics in Bayesian clinical trials relies on…

Methodology · Statistics 2026-03-17 Luke Hagar , Shirin Golchi
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