6 papers
Micro-randomized Trials with Categorical Treatments and Binary Proximal Outcome: Causal Effect Estimation and Sample Size Calculation
Jeremy Lin, Tianchen Qian
Micro-randomized trials (MRTs) provide a framework for evaluating the marginal and moderated effects of mobile health (mHealth) interventions. In many applications, treatments take…
Robust Estimation of Moderated Causal Excursion Odds Ratio in Micro-Randomized Trials
Jiaxin Yu, Tianchen Qian
Micro-randomized trials (MRTs) have become increasingly popular for developing and evaluating mobile health interventions that promote healthy behaviors and manage chronic conditio…
Distal Causal Excursion Effects: Modeling Long-Term Effects of Time-Varying Treatments in Micro-Randomized Trials
Tianchen Qian
Micro-randomized trials (MRTs) play a crucial role in optimizing digital interventions. In an MRT, each participant is sequentially randomized among treatment options hundreds of t…
Dynamic Causal Mediation Analysis for Intensive Longitudinal Data
Tianchen Qian
Intensive longitudinal data, characterized by frequent measurements across numerous time points, are increasingly common due to advances in wearable devices and mobile health techn…
Doubly Robust Estimation of Causal Excursion Effects in Micro-Randomized Trials with Missing Longitudinal Outcomes
Jiaxin Yu, Tianchen Qian
Micro-randomized trials (MRTs) are increasingly utilized for optimizing mobile health interventions, with the causal excursion effect (CEE) as a central quantity for evaluating int…
Modeling Time-Varying Effects of Mobile Health Interventions Using Longitudinal Functional Data from HeartSteps Micro-Randomized Trial
Jiaxin Yu, Tianchen Qian
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 cont…