I am an Associate Professor in the Department of Biostatistics and Bioinformatics at Duke University. I am also affiliated with the Duke Clinical Research Institute and the Consortium for the Holistic Assessment of Risk in Transplant (CHART).
My methodological research focuses on nonparametric, semiparametric, and causal inference methods for comparative effectiveness studies, clinical trials affected by non-compliance, not-so-perfect experiments, and observational studies. My goal is to develop statistical methods that make the best use of the data collected to answer scientific questions while applying principled methods to minimize bias and ensure fair assessments.
The substantive areas of application of my research include public health, biomedical, and social sciences. As a DCRI faculty statistician, I collaborate with clinical researchers to better understand and treat cardiovascular diseases. I am actively involved in the analyses of large registry data including the Society of Thoracic Surgeons (STS) National Database, the STS and American College of Cardiology (ACC) Transcatheter Valve Therapy (TVTR) Registry, and the American Heart Association/American Stroke Association Get With The Guidelines (GTWG).
I am also the head of the analytic team for the Consortium for the Holistic Assessment of Risk in Transplant (CHART). The overarching goal of the CHART is to impart foundational change throughout the entire transplant selection process, by assessing how we collect, organize, and use data to determine patient eligibility for transplant. This multi-center and multi-dimensional health system data goal is to identify and characterize center and system level drivers of inequities in access to transplant (across multiple domains), in order to effectively design interventions that improve equity in access to transplant.
