Respondent-driven sampling (RDS) is a variant of link-tracing, a sampling technique for surveying hard-to-reach communities that takes advantage of community members' social networks to reach potential participants. While the RDS sampling mechanism and associated methods of adjusting for the sampling at the analysis stage are well-documented in the statistical sciences literature, methodological focus has largely been restricted to estimation of population means and proportions (e.g.~prevalence). In this talk, I will present some recent methodological developments in the study of associational questions, the estimation of uncertainty and the assessment of the validity of inference when the social network is partially observed.

Bio: Mamadou Yauck is an Assistant Professor of Statistics at UQAM. He holds a PhD in Statistics from Université Laval. Mamadou’s work focuses on capture-recapture methods for marketing data, link-tracing sampling (especially respondent-driven sampling), causal inference and statistical network data analysis.

Links: (Personal website) https://www.yauckmamadou.com/

(Google Scholar) https://scholar.google.ca/citations?user=TXfJxukAAAAJ&hl=en