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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

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

Stepped wedge cluster-randomized trial (CRTs) designs randomize clusters of individuals to intervention sequences, ensuring that every cluster eventually transitions from a control period to receive the intervention under study by the end…

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…

Mediation analysis has been comprehensively studied for independent data but relatively little work has been done for correlated data, especially for the increasingly adopted stepped wedge cluster randomized trials (SW-CRTs). Motivated by…

Methodology · Statistics 2025-04-03 Zhiqiang Cao , Fan Li

Marginal structural models (MSMs) are often used to estimate causal effects of treatments on survival time outcomes from observational data when time-dependent confounding may be present. They can be fitted using, e.g., inverse probability…

Methodology · Statistics 2023-12-27 Shaun R Seaman , Ruth H Keogh

Machine learning (ML) models are increasingly used as decision-support tools in high-risk domains. Evaluating the causal impact of deploying such models can be done with a randomized controlled trial (RCT) that randomizes users to ML vs.…

Methodology · Statistics 2025-07-17 Jacob M. Chen , Michael Oberst

Cluster-randomized trials (CRTs) are widely used to evaluate interventions delivered at the clinic, practice, or community level. Although standard analyses typically target average treatment effects, such summaries mask potentially…

Methodology · Statistics 2026-04-16 Changjun Li , Xi Fang , Michael O. Harhay , Andrew B. Forbes , F. Perry Wilson , Guangyu Tong , Fan Li

In large observational studies, the case-cohort design is commonly used to reduce the cost associated with covariate measurement. For survival outcomes, literature has suggested that the restricted mean survival time (RMST) be a more…

Methodology · Statistics 2026-05-08 Andy Ni , Wei-En Lu , Bo Lu

There has been significant attention given to developing data-driven methods for tailoring patient care based on individual patient characteristics. Dynamic treatment regimes formalize this through a sequence of decision rules that map…

Methodology · Statistics 2022-02-22 Eric J. Rose , Erica E. M. Moodie , Susan Shortreed

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

While randomized controlled trials (RCTs) are the gold standard for estimating treatment effects in medical research, there is increasing use of and interest in using real-world data for drug development. One such use case is the…

Methodology · Statistics 2021-10-11 Devin Incerti , Michael T Bretscher , Ray Lin , Chris Harbron

Cluster randomized trials (CRTs) offer a practical alternative for addressing logistical challenges and ensuring feasibility in community health, education, and prevention studies, even though randomized controlled trials are considered the…

Methodology · Statistics 2025-10-30 Jooyeon Lee , M. S. , Evan Kwiatkowski , Ph. D

Recently a new experimental approach, the hybrid experimental design (HED), was introduced to enable investigators to answer scientific questions about building behavioral interventions in which human-delivered and digital components are…

Methodology · Statistics 2026-02-26 Mengbing Li , Inbal Nahum-Shani , Walter Dempsey

Background: Stepped wedge cluster randomized trials (SW-CRTs) involve sequential measurements within clusters over time. Initially, all clusters start in the control condition before crossing over to the intervention on a staggered…

Methodology · Statistics 2026-01-21 Jale Basten , Katja Ickstadt , Nina Timmesfeld

Multi-regional clinical trials (MRCTs) play an increasingly crucial role in global pharmaceutical development by expediting data gathering and regulatory approval across diverse patient populations. However, differences in recruitment…

Methodology · Statistics 2024-04-15 Kaiyuan Hua , Hwanhee Hong , Xiaofei Wang

Stepped wedge cluster randomized trials (SW-CRTs) with binary outcomes are increasingly used in prevention and implementation studies. Marginal models represent a flexible tool for analyzing SW-CRTs with population-averaged interpretations,…

Methodology · Statistics 2021-01-05 Fan Li , Hengshi Yu , Paul J. Rathouz , Elizabeth L. Turner , John S. Preisser

Temporally dense single-person "small data" have become widely available thanks to mobile apps and wearable sensors. Many caregivers and self-trackers want to use these data to help a specific person change their behavior to achieve desired…

Methodology · Statistics 2025-09-30 Eric J. Daza , Igor Matias , Logan Schneider

The sequential multiple assignment randomized trial (SMART) is the gold standard trial design to generate data for the evaluation of multi-stage treatment regimes. As with conventional (single-stage) randomized clinical trials, interim…

Methodology · Statistics 2023-09-13 Cole Manschot , Eric Laber , Marie Davidian

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