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projects
The PROviding Mental health Precision Treatment (PROMPT) Precision Health Study
The overall goal of PROMPT is to reduce the burden of depression by 1) increasing capacity in the mental health care system through expanding use of mobile technology-delivered interventions and 2) accelerating recovery from mental illness by better matching patients to pharmacological, psychological, and mobile-based treatments.
The Virtual AppLication-supported ENvironment To INcrease Exercise (VALENTINE) Study
The researchers are trying to determine whether a smartwatch and a mobile application, which together deliver activity and goal setting notifications, can increase activity levels for patients enrolled in cardiac rehabilitation.
publications
Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity
Published in Biometrika, 2022
Estimating Time-Varying Direct and Indirect Causal Excursion Effects with Longitudinal Binary Outcomes
Published in Arxiv, 2022
A Meta-Learning Method for Estimation of Causal Excursion Effects to Assess Time-Varying Moderation
Published in Arxiv, 2023
Incorporating Auxiliary Variables to Improve the Efficiency of Time-Varying Treatment Effect Estimation
Published in Arxiv, 2023
talks
Incorporating auxiliary variables to improve efficiency of time-varying treatment effect estimation
Published:
we present a method for improving causal effect estimation using auxiliary variables, which extends baseline covariate adjustment results beyond single-time-point treatment to time-varying treatment. Existing results concerning asymptotic precision of causal effects are established in the context of randomized controlled trials (RCTs), and it has been demonstrated that covariate adjustment improves or does not hurt asymptotic precision, even when the regression model is incorrect. However, it is still unclear how these covariate adjustment approaches will work with data arising from contexts where treatments, responses, and moderators are time-varying, such as in an MRT. To fill this knowledge gap, we propose a general method called “A2-WCLS”” for auxiliary variable adjusted WCLS with data from MRTs. Under mild conditions, it provides a consistent and asymptotically normal estimate of the moderated causal excursion effect, while retaining or improving estimation efficiency.Through simulation studies and analysis of data from the Intern Health Study, the efficiency gain of the proposed method is demonstrated in comparison to the benchmark WCLS method