Meghan K. Gerety

My disseration work focuses on methods and design considerations for causal inference with challenging longitudinal studies. Specifically, I have worked on problems complicated by estimands that are difficult to define, complex treatment patterns and structures, as well as low event rates and small sample sizes. My first dissertation project discusses appropriate statistical methods for comparing survival outcomes under two different schedules of the same repeated treatment, such as annual versus biennial mammography screening, within the target trial emulation framework. Currently, I am developing a methodological framework for learning tailored multi-component interventions with applications to implementation science and health policy. In future work, I plan to extend this framework to learn optimal sequences of components for multi-component interventions implemented over time.

My other ongoing and past projects include collaborative studies in areas such as nephrology (with the Zee lab) and perinatal health. I have worked directly with clinicians, biologists, and epidemiologists in my past positions, and have experience translating statistical methods and study results for various audiences. During my PhD program, I have had the opporunity to present original research at both clinical and statistical conferences. I love research, and aim to continue innovating statistical methods motivated by and implemented in collaborative projects throughout my career.