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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

Micro-randomized trials (MRTs) are widely used to assess the marginal and moderated effect of mobile health (mHealth) treatments delivered via mobile devices. In many applications, the mHealth treatments are categorical with multiple levels…

Methodology · Statistics 2025-04-23 Jeremy Lin , Tianchen Qian

Technological advancements have made it possible to deliver mobile health interventions to individuals. A novel framework that has emerged from such advancements is the just-in-time adaptive intervention (JITAI), which aims to suggest the…

Methodology · Statistics 2023-07-10 Jing Xu , Xiaoxi Yan , Caroline Figueroa , Joseph Jay Williams , Bibhas Chakraborty

Multi-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many disease areas, it has been argued that their utilisation…

Computation · Statistics 2019-06-24 Michael J Grayling , James MS Wason

Technological advancements in mobile devices have made it possible to deliver mobile health interventions to individuals. A novel intervention framework that emerges from such advancements is the just-in-time adaptive intervention (JITAI),…

Methodology · Statistics 2020-07-29 Jing Xu , Xiaoxi Yan , Caroline Figueroa , Joseph Jay Williams , Bibhas Chakraborty

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

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…

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

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

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

Just-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that use frequent opportunities for the intervention to be adapted such as weekly, daily, or even many times a day. This high intensity of adaptation is…

Human-Computer Interaction · Computer Science 2020-05-13 Ashley E. Walton , Linda M. Collins , Predrag Klasnja , Inbal Nahum-Shani , Mashfiqui Rabbi , Maureen A. Walton , Susan A. Murphy

Sequential Multiple Assignment Randomized Trials (SMARTs) are considered the gold standard for estimation and evaluation of treatment regimes. SMARTs are typically sized to ensure sufficient power for a simple comparison, e.g., the…

Background: Clinical prediction models are increasingly used to inform healthcare decisions, but determining the minimum sample size for their development remains a critical and unresolved challenge. Inadequate sample sizes can lead to…

Machine Learning · Computer Science 2026-03-02 Diana Shamsutdinova , Felix Zimmer , Oyebayo Ridwan Olaniran , Sarah Markham , Daniel Stahl , Gordon Forbes , Ewan Carr

The development of applications for obtaining interpretable results in a simple and summarized manner in multi-state models is a research field with great potential, namely in terms of using open source tools that can be easily implemented…

Computation · Statistics 2022-02-21 Gustavo Soutinho , Luís Meira-Machado

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…

Despite its evanescent nature, statistical power is crucial for planning Partial Least Squares Structural Equation Modelling (PLS-SEM) studies. This brief paper introduces PLS-SEM-power, a Shiny Application and R package that implements the…

Methodology · Statistics 2025-11-20 Alessandro Ansani , Elena Rinallo

Micro-randomized trials (MRTs), which sequentially randomize participants at multiple decision times, have gained prominence in digital intervention development. These sequential randomizations are often subject to certain constraints. In…

Applications · Statistics 2025-01-07 Xiang Meng , Walter Dempsey , Peng Liao , Nick Reid , Pedja Klasnja , Susan Murphy

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 response techniques (RRT) are useful for collecting information on sensitive or confidential attributes in sample surveys. However, such RRTs are rarely used except for pure academic research, as they are deemed to be confusing…

Methodology · Statistics 2021-10-28 G. N. Singh , D. Bhattacharyya , A. Bandyopadhyay

Modern randomization methods in clinical trials are invariably adaptive, meaning that the assignment of the next subject to a treatment group uses the accumulated information in the trial. Some of the recent adaptive randomization methods…

Methodology · Statistics 2024-02-12 Alan R. Vazquez , Weng Kee Wong
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