This spring I gave two talks, one at the New England Statistics Symposium (NESS) hosted by the Department of Statistics, University of Connecticut, and a post-qualifying talk in my home department. Both talks were on my work with my advisor Joe Blitzstein, and both drew heavily on the term homophily. The first talk concerned refined simulation study results concerning design-based estimation, and the second one was about model-based estimation under Respondent-Driven Sampling. For the latter, we consider the data collected within a recent study of populations at high risk of HIV conducted in San Diego. The study took nearly 2 years to complete and was aimed at collecting information describing behavioral and health aspects of the target population. It is a privilege and responsibility to be commissioned to analyze the collected data, as the results of the analysis may be used for subsequent policy decisions. Figure 1 demonstrates the (anonymized) recruitment trees of the study.

Figure 1: San Diego study recruitment trees as functions of HIV status. On the x axis, observation means the HIV status group.