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Related papers: The Micro-Randomized Trial for Developing Digital …

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A dynamic treatment regimen (DTR) is a pre-specified sequence of decision rules which maps baseline or time-varying measurements on an individual to a recommended intervention or set of interventions. Sequential multiple assignment…

Methodology · Statistics 2019-10-23 Brook Luers , Min Qian , Inbal Nahum-Shani , Connie Kasari , Daniel Almirall

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

Item Response Theory (IRT) is a well known method for assessing responses from humans in education and psychology. In education, IRT is used to infer student abilities and characteristics of test items from student responses. Interactions…

Artificial Intelligence · Computer Science 2023-07-20 Antti Keurulainen , Isak Westerlund , Oskar Keurulainen , Andrew Howes

Existing statistical methods for the analysis of micro-randomized trials (MRTs) are designed to estimate causal excursion effects using data from a single MRT. In practice, however, researchers can often find previous MRTs that employ…

Methodology · Statistics 2025-05-13 Easton Huch , Inbal Nahum-Shani , Lindsey Potter , Cho Lam , David W. Wetter , Walter Dempsey

Adaptive interventions, aka dynamic treatment regimens, are sequences of pre-specified decision rules that guide the provision of treatment for an individual given information about their baseline and evolving needs, including in response…

Methodology · Statistics 2024-05-02 Wenchu Pan , Daniel Almirall , Amy M. Kilbourne , Andrew Quanbeck , Lu Wang

The micro-randomized trial (MRT) is a new experimental design which allows for the investigation of the proximal effects of a "just-in-time" treatment, often provided via a mobile device as part of a mobile health intervention. As with a…

Methodology · Statistics 2020-08-07 Nicholas J. Seewald , Ji Sun , Peng Liao

Mobile health is a rapidly developing field in which behavioral treatments are delivered to individuals via wearables or smartphones to facilitate health-related behavior change. Micro-randomized trials (MRT) are an experimental design for…

Methodology · Statistics 2019-05-13 Tianchen Qian , Predrag Klasnja , Susan A. Murphy

Micro-randomized trials (MRTs) play a crucial role in optimizing digital interventions. In an MRT, each participant is sequentially randomized among treatment options hundreds of times. While the interventions tested in MRTs target…

Methodology · Statistics 2025-09-04 Tianchen Qian

Not only does mobile health technology enable researchers to track changes in multiple longitudinal outcomes of interest and to record the occurrence of health-related events over time, but it also allows for the delivery of repeated…

Dynamic treatment regimes (DTRs) are personalized, adaptive, multi-stage treatment plans that adapt treatment decisions both to an individual's initial features and to intermediate outcomes and features at each subsequent stage, which are…

Machine Learning · Statistics 2022-09-22 Yichun Hu , Nathan Kallus

Rapidly Exploring Random Tree (RRT) algorithms, notably used for nonholonomic vehicle navigation in complex environments, are often not thoroughly evaluated for their specific challenges. This paper presents a first such comparison study of…

Robotics · Computer Science 2025-01-14 Trym Tengesdal , Tom Arne Pedersen , Tor Arne Johansen

In a sequential multiple-assignment randomized trial (SMART), a sequence of treatments is given to a patient over multiple stages. In each stage, randomization may be done to allocate patients to different treatment groups. Even though…

Methodology · Statistics 2024-01-09 Rik Ghosh , Bibhas Chakraborty , Inbal Nahum-Shani , Megan E. Patrick , Palash Ghosh

In high-dimensional robotic path planning, traditional sampling-based methods often struggle to efficiently identify both feasible and optimal paths in complex, multi-obstacle environments. This challenge is intensified in robotic…

Randomized controlled trials (RCTs) can be used to generate guarantees on treatment effects. However, RCTs often spend unnecessary resources exploring sub-optimal treatments, which can reduce the power of treatment guarantees. To address…

Computers and Society · Computer Science 2024-10-16 Santiago Cortes-Gomez , Naveen Raman , Aarti Singh , Bryan Wilder

We developed a study design for rare disease clinical trials (RDTs) that efficiently evaluate treatments, promotes access to new treatments during treatment development, and optimizes healthcare resource utilization for future treatment…

Applications · Statistics 2016-07-04 Jian Yong , Sohaib H. Mohammad , Yan Yuan

Adaptive experiments are used extensively in online platforms, healthcare and biotechnology, and a variety of other settings. In many of these applications, the main goal is not to precisely estimate a treatment effect, but to demonstrate…

Statistics Theory · Mathematics 2026-03-10 Guido Imbens , Lorenzo Masoero , Alexander Rakhlin , Thomas S. Richardson , Suhas Vijaykumar

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

Robot-Assisted Therapy (RAT) has successfully been used in Human Robot Interaction (HRI) research by including social robots in health-care interventions by virtue of their ability to engage human users in both social and emotional…

Advances in wearables and digital technology now make it possible to deliver behavioral mobile health interventions to individuals in their everyday life. The micro-randomized trial (MRT) is increasingly used to provide data to inform the…

Methodology · Statistics 2020-07-30 Tianchen Qian , Hyesun Yoo , Predrag Klasnja , Daniel Almirall , Susan A. Murphy

Digital behaviour change systems increasingly rely on repeated, system-initiated messages to support users in everyday contexts. LLMs enable these messages to be personalised consistently across interactions, yet it remains unclear whether…

Human-Computer Interaction · Computer Science 2026-03-02 Dominik P. Hofer , David Haag , Rania Islambouli , Jan D. Smeddinck