Hi there! Welcome.
I’m a PhD Candidate advised by Dr. Hwanhee Hong in the Duke School of Medicine, Department of Biostatistics & Bioinformatics. I am interested in Bayesian hierarchical modeling in the regards to data integration, but more specifically utilized within comparative effectiveness research. While I work with combing data sources, the primary goal is to better understand and uncover health disparities that is limited through data availability. Simultaneously, I am interested in teaching and ultimately begin able to educate a new generation of statisticians.
Lately
I have been working on my dissertation titled, Bayesian Hierarchical Models for the Combination of Data from Heterogeneous Sources. In general, harnessing information from multiple data sources is recognized for yielding more comprehensive and reliable results compared to relying solely on a single source. However, several key challenges arise in this process, including variability in quality of sources, missingness in key variables, and differences in populations of which each data set were sample. All three of my aims provide methods under the context of Bayesian Hierarchical modeling that address such key issues.
