Hard-to-reach population sampling

Population Size Estimation Using Multiple Respondent-Driven Sampling Surveys

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 …

Network Model-Assisted Inference from Respondent-Driven Sampling Data

Respondent-driven sampling is a widely used method for sampling hard-to-reach human populations by link tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond …

Estimating the Size of Populations at High Risk for HIV using Respondent-Driven Sampling Data

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 …

Estimating Hidden Population Size using Respondent-Driven Sampling Data

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 …

Respondent-Driven Sampling: An Assessment of Current Methodology

Respondent-driven sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure to expand …