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Clinical trials with time-to-event endpoints, such as overall survival (OS) or progression-free survival (PFS), are fundamental for evaluating new treatments, particularly in immuno-oncology. However, modern therapies, such as…

Methodology · Statistics 2025-09-10 James Salsbury , Jeremy Oakley , Steven Julious , Lisa Hampson

A multi-arm multi-stage trial is a multi-arm trial which includes interim analyses - analysing the data at certain specified points, generally discontinuing treatments which are concluded to not work and proceeding with the remainder. It is…

Methodology · Statistics 2022-11-14 Martin Law

This study designs an adaptive experiment for efficiently estimating average treatment effects (ATEs). In each round of our adaptive experiment, an experimenter sequentially samples an experimental unit, assigns a treatment, and observes…

Methodology · Statistics 2024-06-21 Masahiro Kato , Akihiro Oga , Wataru Komatsubara , Ryo Inokuchi

Adaptable computing is an increasingly important paradigm that specializes system resources to variable application requirements, environmental conditions, or user requirements. Adapting computing resources to variable application…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-03 Keeley Criswell , Tosiron Adegbija

Breakthroughs in cancer biology have defined new research programs emphasizing the development of therapies that target specific pathways in tumor cells. Innovations in clinical trial design have followed with master protocols defined by…

Methodology · Statistics 2020-07-09 Alexander M. Kaizer , Joseph S. Koopmeiners , Nan Chen , Brian P. Hobbs

Dynamic treatment regimes are sequential decision rules that adapt treatment according to individual time-varying characteristics and outcomes to achieve optimal effects, with applications in precision medicine, personalized…

Methodology · Statistics 2025-10-24 Yuanshan Gao , Yang Bai , Yifan Cui

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

Cluster-level dynamic treatment regimens can be used to guide sequential, intervention or treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level DTR, the…

Methodology · Statistics 2016-07-15 Timothy NeCamp , Amy Kilbourne , Daniel Almirall

With increasing interest in adaptive clinical trial designs, challenges are present to drug supply chain management which may offset the benefit of adaptive designs. Thus, it is necessary to develop an optimization tool to facilitate the…

Applications · Statistics 2023-10-16 Jincheng Pang , Hong Yan , Zoe Hua

A common problem faced in clinical studies is that of estimating the effect of the most effective (e.g., the one having the largest mean) treatment among $k~(\geq2)$ available treatments. The most effective treatment is adjudged based on…

Statistics Theory · Mathematics 2022-09-20 Masihuddin , Neeraj Misra

We consider the optimal experimental design problem of allocating subjects to treatment or control when subjects participate in multiple, separate controlled experiments within a short time-frame and subject covariate information is…

Methodology · Statistics 2024-12-16 William Fisher , Qiong Zhang , Lulu Kang , Xinwei Deng

The present paper deals with the problem of allocating patients to two competing treatments in the presence of covariates or prognostic factors in order to achieve a good trade-off among ethical concerns, inferential precision and…

Methodology · Statistics 2012-08-17 Alessandro Baldi Antognini , Maroussa Zagoraiou

This article proposes a novel adaptive design algorithm that can be used to find optimal treatment allocations in N-of-1 clinical trials. This new methodology uses two Laplace approximations to provide a computationally efficient estimate…

Computation · Statistics 2020-07-30 S. G. Jagath Senarathne , Antony M. Overstall , James M. McGree

Estimating the effects of interventions in networks is complicated when the units are interacting, such that the outcomes for one unit may depend on the treatment assignment and behavior of many or all other units (i.e., there is…

Methodology · Statistics 2014-08-15 Dean Eckles , Brian Karrer , Johan Ugander

Randomized experiments can provide unbiased estimates of sample average treatment effects. However, estimates of population treatment effects can be biased when the experimental sample and the target population differ. In this case, the…

Methodology · Statistics 2022-11-10 Wenqi Shi , Xi Lin

Clinical trials involving multiple treatments utilize randomization of the treatment assignments to enable the evaluation of treatment efficacies in an unbiased manner. Such evaluation is performed in post hoc studies that usually use…

Artificial Intelligence · Computer Science 2018-09-10 Yogatheesan Varatharajah , Brent Berry , Sanmi Koyejo , Ravishankar Iyer

Sequential, multiple assignment randomized trials (SMARTs), which assist in the optimization of adaptive interventions, are growing in popularity in education and behavioral sciences. This is unsurprising, as adaptive interventions reflect…

Methodology · Statistics 2023-09-26 Timothy Lycurgus , Amy Kilbourne , Daniel Almirall

Suppose that we intend to perform an experiment consisting of a set of independent trials. The mean value of the response of each trial is assumed to be equal to the sum of the effect of the treatment selected for the trial, and some…

Statistics Theory · Mathematics 2016-12-21 Samuel Rosa , Radoslav Harman

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

Selective recruitment designs preferentially recruit individuals that are estimated to be statistically informative onto a clinical trial. Individuals that are expected to contribute less information have a lower probability of recruitment.…

Statistics Theory · Mathematics 2017-05-31 James E. Barrett
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