One strand of my work uses quantitative methods to investigate individual and network correlates of victimization, with the bulk of this research involving intimate partner violence (IPV) outcomes. In my dissertation, I utilize social network analysis, syndemic, and social complexity frameworks to examine the role of IPV in queer men’s sexual and drug use partnerships, doing so in three interrelated papers. In the first, I conduct a systematic review and meta-analysis of associations between queer men’s IPV victimization and network structural attributes reported in existing literature. This review helps guide the analyses of my latter two papers, in which I explore how queer men’s IPV victimization is associated with (1) the structure of their sexual network ties, and (2) illicit drug use within these sexual network ties. I study these dynamics using secondary data from RADAR, a National Institute on Drug Abuse-funded cohort study (2014) of sexual relationship patterns, substance use, and other health outcomes among nearly 1,100 Chicago-area queer men. For these two papers, I rely on egocentric exponential random graph models (ego-ERGMs), a novel method for statistical inference on tie formation that uses egocentric, rather than sociocentric (“complete”) network data. Collectively, my dissertation papers highlight significant links between queer men’s sociodemographic factors (e.g., race, HIV status), IPV victimization, and sexual networks.