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Related papers: Network Interference in Micro-Randomized Trials

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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

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

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…

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

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

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

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 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

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

Randomized experiments are widely used to estimate the causal effects of a proposed treatment in many areas of science, from medicine and healthcare to the physical and biological sciences, from the social sciences to engineering, to public…

Methodology · Statistics 2022-11-30 Christina Lee Yu , Edoardo M Airoldi , Christian Borgs , Jennifer T Chayes

Randomised Controlled Trials (RCTs) are the gold standard for estimating treatment effects across many fields of science. Technology companies have adopted A/B-testing methods as a modern RCT counterpart, where end-users are randomly…

Social and Information Networks · Computer Science 2024-09-20 Olivier Jeunen

Randomized experiments are a powerful methodology for data-driven evaluation of decisions or interventions. Yet, their validity may be undermined by network interference. This occurs when the treatment of one unit impacts not only its…

Methodology · Statistics 2024-10-08 Sadegh Shirani , Mohsen Bayati

Experiments on online marketplaces and social networks suffer from interference, where the outcome of a unit is impacted by the treatment status of other units. We propose a framework for modeling interference using a ubiquitous deployment…

Methodology · Statistics 2023-08-21 Ariel Boyarsky , Hongseok Namkoong , Jean Pouget-Abadie

Network interference, where the outcome of an individual is affected by the treatment assignment of those in their social network, is pervasive in real-world settings. However, it poses a challenge to estimating causal effects. We consider…

Methodology · Statistics 2024-02-06 Mayleen Cortez-Rodriguez , Matthew Eichhorn , Christina Lee Yu

Estimating the treatment effect within network structures is a key focus in online controlled experiments, particularly for social media platforms. We investigate a scenario where the unit-level outcome of interest comprises a series of…

Methodology · Statistics 2025-05-28 Yilin Li , Lu Deng , Yong Wang , Wang Miao

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

Randomized controlled trials are not only the golden standard in medicine and vaccine trials but have spread to many other disciplines like behavioral economics, making it an important interdisciplinary tool for scientists. When designing…

Methodology · Statistics 2021-11-30 Tassilo Schwarz

Estimation of social influence in networks can be substantially biased in observational studies due to homophily and network correlation in exposure to exogenous events. Randomized experiments, in which the researcher intervenes in the…

Social and Information Networks · Computer Science 2017-09-28 Sean J. Taylor , Dean Eckles

No man is an island, as individuals interact and influence one another daily in our society. When social influence takes place in experiments on a population of interconnected individuals, the treatment on a unit may affect the outcomes of…

Methodology · Statistics 2017-08-30 Edward K. Kao
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