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Clinicians and researchers alike are increasingly interested in how best to personalize interventions. A dynamic treatment regimen (DTR) is a sequence of pre-specified decision rules which can be used to guide the delivery of a sequence of…

Cross-validation is a widely used technique for evaluating the performance of prediction models, ranging from simple binary classification to complex precision medicine strategies. It helps correct for optimism bias in error estimates,…

Personalized medicine has gained much popularity recently as a way of providing better healthcare by tailoring treatments to suit individuals. Our research, motivated by the UK INTERVAL blood donation trial, focuses on estimating the…

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

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…

In single-arm phase II oncology trials, the most popular choice of design is Simon's two-stage design, which allows early stopping at one interim analysis. However, the expected trial sample size can be reduced further by allowing…

Methodology · Statistics 2019-09-09 Martin Law , Michael J. Grayling , Adrian P. Mander

Dynamic treatment regimens (DTRs) aim at tailoring individualized sequential treatment rules that maximize cumulative beneficial outcomes by accommodating patients' heterogeneity in decision-making. For many chronic diseases including type…

Methodology · Statistics 2024-04-23 Mochuan Liu , Yuanjia Wang , Haoda Fu , Donglin Zeng

Longitudinal cluster randomized trials (L-CRTs) are increasingly used to evaluate the cost-effectiveness of healthcare interventions across multiple assessment periods, yet design methods for powering these trials remain underdeveloped.…

Methodology · Statistics 2026-03-20 Hao Wang , Jingxia Liu , Drew B. Cameron , Jiaqi Tong , Donna Spiegelman , Daniella Meeker , Fan Li

Randomized experiments are the gold standard for estimating the causal effects of an intervention. In the simplest setting, each experimental unit is randomly assigned to receive treatment or control, and then the outcomes in each treatment…

Methodology · Statistics 2020-06-05 Guillaume Basse , Yi Ding , Panos Toulis

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

We show that bootstrap methods based on the positivity of probability measures provide a systematic framework for studying both synchronous and asynchronous nonequilibrium stochastic processes on infinite lattices. First, we formulate…

Statistical Mechanics · Physics 2025-11-12 Minjae Cho

One common approach for dose optimization is a two-stage design, which initially conducts dose escalation to identify the maximum tolerated dose (MTD), followed by a randomization stage where patients are assigned to two or more doses to…

Methodology · Statistics 2024-11-11 Yixuan Zhao , Rachael Liu , Jianchang Lin , Ying Yuan

It is a common practice in randomized clinical trials with the standard survival outcome to follow patients until a prespecified number of events have been observed, a type of trial known as the event-driven trial. The event-driven design…

Methodology · Statistics 2026-02-10 Jingwen Zhang , Satoshi Hattori

Randomized saturation designs are a family of designs which assign a possibly different treatment proportion to each cluster of a population at random. As a result, they generalize the well-known (stratified) completely randomized designs…

Methodology · Statistics 2022-03-21 Chencheng Cai , Jean Pouget-Abadie , Edoardo M. Airoldi

Bootstrapping is often applied to get confidence limits for semiparametric inference of a target parameter in the presence of nuisance parameters. Bootstrapping with replacement can be computationally expensive and problematic when…

Purpose: Vision-based robot tool segmentation plays a fundamental role in surgical robots and downstream tasks. CaRTS, based on a complementary causal model, has shown promising performance in unseen counterfactual surgical environments in…

Robotics · Computer Science 2022-12-02 Hao Ding , Jie Ying Wu , Zhaoshuo Li , Mathias Unberath

Clinical prediction models are increasingly used to support patient care, yet many deep learning-based approaches remain unstable, as their predictions can vary substantially when trained on different samples from the same population. Such…

Machine Learning · Computer Science 2026-02-13 Sara Matijevic , Christopher Yau

We propose a methodology for constructing confidence regions with partially identified models of general form. The region is obtained by inverting a test of internal consistency of the econometric structure. We develop a dilation bootstrap…

Econometrics · Economics 2021-02-10 Alfred Galichon , Marc Henry

The authors propose robust adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan applied during the first fractions should be able to handle…

Optimization and Control · Mathematics 2018-10-01 Michelle Böck , Anders Forsgren , Kjell Eriksson , Björn Hårdemark

Group sequential designs (GSDs) are well established and the most commonly used adaptive design in confirmatory clinical trials with interim analyses. However, they remain underutilised, and their implementation involves unique theoretical…

Methodology · Statistics 2025-09-09 Zhangyi He , Suzie Cro , Laurent Billot

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…