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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…

Single-subject health data are becoming increasingly available thanks to advances in self-tracking technology (e.g., wearable devices, mobile apps, sensors, implants). Many users and health caregivers seek to use such observational time…

Applications · Statistics 2019-01-23 Eric Jay Daza

Researchers increasingly leverage movement across multiple treatments to estimate causal effects. While these "mover regressions" are often motivated by a linear constant-effects model, it is not clear what they capture under weaker…

Econometrics · Economics 2018-04-19 Peter Hull

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

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

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

Individual-level human mobility prediction has emerged as a significant topic of research with applications in infectious disease monitoring, child, and elderly care. Existing studies predominantly focus on the microscopic aspects of human…

Machine Learning · Computer Science 2025-08-20 Yueyang Liu , Lance Kennedy , Ruochen Kong , Joon-Seok Kim , Andreas Züfle

An optimal dynamic treatment regime (DTR) is a sequence of decision rules aimed at providing the best course of treatments individualized to patients. While conventional DTR estimation uses longitudinal data, such data can also be…

Methodology · Statistics 2025-02-06 Larry Dong , Eleanor Pullenayegum , Rodolphe Thiébaut , Olli Saarela

An optimal individualized treatment rule (ITR) is a function that takes a patient's characteristics, such as demographics, biomarkers, and treatment history, and outputs a treatment that is expected to give the best outcome for that…

Methodology · Statistics 2026-02-05 Augustine Wigle , Erica E. M. Moodie

In precision medicine, Dynamic Treatment Regimes (DTRs) are treatment protocols that adapt over time in response to a patient's observed characteristics. A DTR is a set of decision functions that takes an individual patient's information as…

Methodology · Statistics 2022-03-17 Cong Jiang , Michael Wallace , Mary Thompson

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

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

An individualized treatment rule (ITR) is a decision rule that aims to improve individual patients health outcomes by recommending optimal treatments according to patients specific information. In observational studies, collected data may…

Methodology · Statistics 2023-10-03 Zeyu Bian , Erica EM Moodie , Susan M Shortreed , Sylvie D Lambert , Sahir Bhatnagar

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

Individuals with bipolar disorder tend to cycle through disease states such as depression and mania. The heterogeneous nature of disease across states complicates the evaluation of interventions for bipolar disorder patients, as varied…

Identifying patients who benefit from a treatment is a key aspect of personalized medicine, which allows the development of individualized treatment rules (ITRs). Many machine learning methods have been proposed to create such rules.…

Individualized treatment rule (ITR) recommends treatment on the basis of individual patient characteristics and the previous history of applied treatments and their outcomes. Despite the fact there are many ways to estimate ITR with binary…

Methodology · Statistics 2017-08-15 Pavel Shvechikov , Evgeniy Riabenko

Observational cohort studies are increasingly being used for comparative effectiveness research to assess the safety of therapeutics. Recently, various doubly robust methods have been proposed for average treatment effect estimation by…

Methodology · Statistics 2025-03-11 Xiaoqing Tan , Shu Yang , Wenyu Ye , Douglas E. Faries , Ilya Lipkovich , Zbigniew Kadziola

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…

Individualized treatment rules (ITR) can improve health outcomes by recognizing that patients may respond differently to treatment and assigning therapy with the most desirable predicted outcome for each individual. Flexible and efficient…

Methodology · Statistics 2017-09-25 Brent R. Logan , Rodney Sparapani , Robert E. McCulloch , Purushottam W. Laud
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