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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
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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
teaching
Causal inference
Part III Master Level Class, CMS, 2025
This is a Part III 16-lecture class in DPMMS, University of Cambridge