Primary Submission Category: Heterogeneous Treatment Effects
Modeling Time-Varying Effects of Mobile Health Interventions Using Longitudinal Functional Data from HeartSteps Micro-Randomized Trial
Authors: Jiaxin Yu, Predrag Klasnja, Susan Murphy, Tianchen Qian,
Presenting Author: Jiaxin Yu*
Understanding how the effect of a mobile health intervention varies over time and with contextual information is critical for both optimizing the intervention and advancing domain knowledge. This analysis aims to assess how a push notification suggesting physical activity influences individuals’ step count and how such influence varies over time, using data from the HeartSteps micro-randomized trial (MRT). The statistical challenges include the time-varying treatments and the longitudinal functional step count measurements. We propose the first semiparametric causal excursion effect model with varying coefficients to model the time-varying effects within a decision point and across decision points in an MRT. The proposed model incorporates double time indices to accommodate the longitudinal functional outcome, enabling the assessment of time-varying effect moderation by contextual variables. We propose a two-stage causal effect estimator that is robust against a misspecified high-dimensional outcome regression model. We establish asymptotic theory and conduct simulation studies to validate the proposed estimator. Our analysis provides new insights into individuals’ change in response profiles (such as how soon a response occurs) due to the activity suggestions, how such changes differ by the type of suggestion they receive, and how such changes depend on other contextual information such as being recently sedentary and the day being a weekday.