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The micro-randomized trial (MRT) is a sequential randomized experimental design to empirically evaluate the effectiveness of mobile health (mHealth) intervention components that may be delivered at hundreds or thousands of decision points.…

Methodology · Statistics 2021-12-14 Jieru Shi , Zhenke Wu , Walter Dempsey

The use and development of mobile interventions are experiencing rapid growth. In "just-in-time" mobile interventions, treatments are provided via a mobile device and they are intended to help an individual make healthy decisions "in the…

Methodology · Statistics 2020-07-23 Peng Liao , Predrag Klasnja , Ambuj Tewari , Susan A. Murphy

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

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

Advances in wearable technologies and health interventions delivered by smartphones have greatly increased the accessibility of mobile health (mHealth) interventions. Micro-randomized trials (MRTs) are designed to assess the effectiveness…

Methodology · Statistics 2025-08-12 Jieru Shi , Walter Dempsey

Although there is much excitement surrounding the use of mobile and wearable technology for the purposes of delivering interventions as people go through their day-to-day lives, data analysis methods for constructing and optimizing digital…

The micro-randomized trial (MRT) is an experimental design that can be used to develop optimal mobile health interventions. In MRTs, interventions in the form of notifications or messages are sent through smart phones to individuals,…

Methodology · Statistics 2022-02-14 Shuangning Li , Stefan Wager

Micro-randomized trials (MRTs) have become increasingly popular for developing and evaluating mobile health interventions that promote healthy behaviors and manage chronic conditions. The recently proposed causal excursion effects have…

Methodology · Statistics 2025-09-26 Jiaxin Yu , Tianchen Qian

To optimize mobile health interventions and advance domain knowledge on intervention design, it is critical to understand how the intervention effect varies over time and with contextual information. This study aims to assess how a push…

Applications · Statistics 2024-10-22 Jiaxin Yu , Tianchen Qian

Mobile health studies can leverage longitudinal sensor data from smartphones to guide the application of personalized medical interventions. In this paper, we propose that adoption of an instrumental variable approach for randomized trials…

Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and anywhere. Increasingly the delivery of…

Applications · Statistics 2017-11-13 Walter Dempsey , Peng Liao , Santosh Kumar , Susan A. Murphy

Construction of just-in-time adaptive interventions, such as prompts delivered by mobile apps to promote and maintain behavioral change, requires knowledge about time-varying moderated effects to inform when and how we deliver intervention…

Methodology · Statistics 2022-12-06 Jieru Shi , Zhenke Wu , Walter Dempsey

Just-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that use frequent opportunities for the intervention to be adapted--weekly, daily, or even many times a day. The micro-randomized trial (MRT) has emerged…

Micro-randomized trials (MRTs) are increasingly utilized for optimizing mobile health interventions, with the causal excursion effect (CEE) as a central quantity for evaluating interventions under policies that deviate from the experimental…

Methodology · Statistics 2024-11-19 Jiaxin Yu , Tianchen Qian

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

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

Randomized Controlled Trials (RCT) are the current gold standards to empirically measure the effect of a new drug. However, they may be of limited size and resorting to complementary non-randomized data, referred to as observational, is…

Methodology · Statistics 2025-06-11 Ahmed Boughdiri , Julie Josse , Erwan Scornet

Cluster-randomized trials (CRTs) are widely used to evaluate group-level interventions and increasingly collect multiple outcomes capturing complementary dimensions of benefit and risk. Investigators often seek a single global summary of…

Methodology · Statistics 2026-01-22 Xinyuan Chen , Fan Li

There is a growing interest in leveraging the prevalence of mobile technology to improve health by delivering momentary, contextualized interventions to individuals' smartphones. A just-in-time adaptive intervention (JITAI) adjusts to an…

Other Statistics · Statistics 2018-12-31 Nicholas J. Seewald , Shawna N. Smith , Andy Jinseok Lee , Predrag Klasnja , Susan A. Murphy

Restricted mean survival time (RMST) is gaining attention as a measure to quantify the treatment effect on survival outcomes in randomized clinical trials. Several methods to determine sample size based on the RMST-based tests have been…

Methodology · Statistics 2022-12-19 Satoshi Hattori , Hajime Uno
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