We develop a method for improved estimation of a participant’s inclusion probability based on their network size (degree) as well as other information.
Respondent-driven sampling (RDS) is commonly used to study hard-to-reach populations since traditional methods are unable to efficiently survey members due to the typically highly stigmatized nature of the population. The number of people in these …
The study of hard-to-reach populations presents significant challenges. Typically, a sampling frame is not available, and population members are difficult to identify or recruit from broader sampling frames. This is especially true of populations at …
Respondent-Driven Sampling (RDS) is n approach to sampling design and inference in hard-to-reach human populations. It is often used in situations where the target population is rare and/or stigmatized in the larger population, so that it is …