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Title:听Sampling from Networks: Respondent-Driven Sampling.

Abstract: Respondent-driven sampling (RDS) is an approach to acquiring data from individuals who may be unwilling to participate in a traditional study, often because of social stigma. In RDS, the study recruitment protocol generates a large number of recruitment waves, with each successive participants being asked to recruit additional participants within their social network starting from initial seed participants. In this talk, we present strategies for simulating RDS samples with known network and sample characteristics. We then present sensitivity analyses to assess the accuracy of simulated RDS samples. We apply our methodology to a dataset about HIV transmission among gay, bisexual and queer men, including trans-men and men who have sex with men in Montreal.

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