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Consider a general setting in which data on an outcome is collected in two `groups' at two time periods, with certain group-periods deemed `treated' and others `untreated'. A special case is the canonical Difference-in-Differences (DiD)…

Methodology · Statistics 2025-09-15 Zach Shahn , Laura Hatfield

The call for patient-focused drug development is loud and clear, as expressed in the 21st Century Cures Act and in recent guidelines and initiatives of regulatory agencies. Among the factors contributing to modernized drug development and…

When the infection prevalence of a disease is low, Dorfman showed 80 years ago that testing groups of people can prove more efficient than testing people individually. Our goal in this paper is to propose new group testing algorithms that…

Methodology · Statistics 2020-07-23 Marco Cuturi , Olivier Teboul , Quentin Berthet , Arnaud Doucet , Jean-Philippe Vert

In clinical trials, multiple outcomes of different priorities commonly occur as the patient's response may not be adequately characterized by a single outcome. Win statistics are appealing summary measures for between-group difference at…

Methodology · Statistics 2025-06-04 Ying Cui , Bo Huang , Gaohong Dong , Ryuji Uozumi , Lu Tian

Estimation using pooled sampling has long been an area of interest in the group testing literature. Such research has focused primarily on the assumed use of fixed sampling plans (i), although some recent papers have suggested alternative…

Statistics Theory · Mathematics 2017-03-27 Gregory Haber , Yaakov Malinovsky , Paul Albert

We investigate the optimal design of experimental studies that have pre-treatment outcome data available. The average treatment effect is estimated as the difference between the weighted average outcomes of the treated and control units. A…

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

In bioequivalence design, power analyses dictate how much data must be collected to detect the absence of clinically important effects. Power is computed as a tail probability in the sampling distribution of the pertinent test statistics.…

Methodology · Statistics 2025-01-27 Luke Hagar , Nathaniel T. Stevens

Randomised controlled trials aim to assess the impact of one (or more) health interventions relative to other standard interventions. RCTs sometimes use an ordinal outcome, which is an endpoint that comprises of multiple, monotonically…

Methodology · Statistics 2022-08-15 Chris J. Selman , Katherine J. Lee , Robert K. Mahar

A stepped wedge cluster randomized trial is a type of longitudinal cluster design that sequentially switches clusters to intervention over time until all clusters are treated. While the traditional posttest-only parallel design requires…

Applications · Statistics 2021-01-05 Fan Li

This paper studies prototypical strategies to sequentially aggregate independent decisions. We consider a collection of agents, each performing binary hypothesis testing and each obtaining a decision over time. We assume the agents are…

Applications · Statistics 2010-08-30 Sandra H. Dandach , Ruggero Carli , Francesco Bullo

One way to investigate the precision of estimates likely to result from planned experiments and planned epidemiological studies is to simulate a large number of possible outcomes and analyse the sets of possible results. This appears to be…

Computation · Statistics 2013-06-28 G. K. Robinson , L. M. Ryan

Randomization tests are a popular method for testing causal effects in clinical trials with finite-sample validity. In the presence of heterogeneous treatment effects, it is often of interest to select a subgroup that benefits from the…

Methodology · Statistics 2025-04-29 Zijun Gao

We consider continuous-time survival or more general event-history settings, where the aim is to infer the causal effect of a time-dependent treatment process. This is formalised as the effect on the outcome event of a (possibly…

Methodology · Statistics 2024-04-23 Kjetil Røysland , Pål Ryalen , Mari Nygård , Vanessa Didelez

This paper presents a novel control design for vehicular formations, which is an alternative to the conventional second-order consensus protocol. The design is motivated by the closed-loop system, which we construct as first-order systems…

Optimization and Control · Mathematics 2024-02-26 Jonas Hansson , Emma Tegling

We consider the problem of designing experiments for the comparison of two regression curves describing the relation between a predictor and a response in two groups, where the data between and within the group may be dependent. In order to…

Statistics Theory · Mathematics 2021-01-15 Kirsten Schorning , Holger Dette

Stochastic processes offer a flexible mathematical formalism to model and reason about systems. Most analysis tools, however, start from the premises that models are fully specified, so that any parameters controlling the system's dynamics…

Systems and Control · Computer Science 2017-01-11 Luca Bortolussi , Guido Sanguinetti

In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects…

Methodology · Statistics 2021-05-28 Iavor Bojinov , Ashesh Rambachan , Neil Shephard

Sequential multiple assignment randomized trials mimic the actual treatment processes experienced by physicians and patients in clinical settings and inform the comparative effectiveness of dynamic treatment regimes. In such trials,…

Methodology · Statistics 2025-04-07 Zi Wang , Yu Cheng , Abdus S. Wahed

The mean completion time of a stochastic process may be rendered finite and minimised by a judiciously chosen restart protocol, which may either be stochastic or deterministic. Here we study analytically an arbitrary stochastic search…

Quantitative Methods · Quantitative Biology 2016-09-14 Kabir Husain , Sandeep Krishna