Sample Heterogeneity across Recruitment Waves in Respondent-Driven Sampling Studies

Thomas M. Menino Convention & Exhibition Center 

Respondent-driven sampling (RDS) leverages social networks to recruit participants. Once seeds are recruited by the research team, participants recruit others through chain referrals, and the sample size accumulates over successive waves. This process may demonstrate a key methodological strength of RDS: particularly how RDS can introduce heterogeneity into a sample.
This study examines participant characteristics across recruitment waves in two distinctive RDS studies: (1) an in-person RDS study that targeted persons who inject drugs in Southeast Michigan; and (2) a web RDS survey that sampled adults with Korean heritage in the U.S. For each study, we selected variables spanning a range of thematic domains (e.g., drug use behavior, immigration history) and summarized them through multidimensional principal components analysis. We then visualized the principal components by wave to illustrate whether RDS introduces sample heterogeneity. Further, we compared the levels and patterns of sample heterogeneity between the two RDS studies. This work is supported by the National Secure Data Service Demonstration project, aiming to strengthen efficiencies in data collection efforts.

Respondent-driven sampling

principal components analysis

hard-to-reach population 

Survey Research Methods Section