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The Micro-Randomized Trial for Developing Digital Interventions: Experimental Design Considerations
Just-in-time adaptive interventions (JITAIs) are time-varying adaptive i...
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The Micro-Randomized Trial for Developing Digital Interventions: Data Analysis Methods
Although there is much excitement surrounding the use of mobile and wear...
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Streamlined Empirical Bayes Fitting of Linear Mixed Models in Mobile Health
To effect behavior change a successful algorithm must make high-quality ...
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Inference for Batched Bandits
As bandit algorithms are increasingly utilized in scientific studies, th...
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Estimating Time-Varying Causal Excursion Effect in Mobile Health with Binary Outcomes
Advances in wearables and digital technology now make it possible to del...
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Linear mixed models under endogeneity: modeling sequential treatment effects with application to a mobile health study
Mobile health is a rapidly developing field in which behavioral treatmen...
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Practical Considerations for Data Collection and Management in Mobile Health Micro-randomized Trials
There is a growing interest in leveraging the prevalence of mobile techn...
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The stratified micro-randomized trial design: sample size considerations for testing nested causal effects of time-varying treatments
Technological advancements in the field of mobile devices and wearable s...
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An Actor-Critic Contextual Bandit Algorithm for Personalized Mobile Health Interventions
Increasing technological sophistication and widespread use of smartphone...
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Active Learning for Developing Personalized Treatment
The personalization of treatment via bio-markers and other risk categori...
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