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Activity Number: 492
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #321065 View Presentation
Title: Regression Models and Tests for Recruitment Dynamics in Respondent-Driven Sampling
Author(s): Li Zeng* and Forrest Crawford and Jianghong Li
Companies: Yale University and Yale University and Yale University
Keywords: injection drug use ; network sampling ; social link tracing ; survival analysis

Respondent-driven Sampling (RDS) is a recruitment procedure for surveys of hidden or hard to reach populations. In RDS, enrolled subjects get extra rewards for successful recruitment of their friends who are also in the target network. The quality of statistical estimates from RDS depends on assumptions about the nature of the recruitment process and the social network underlying the target population. Selection bias may affect estimates from RDS surveys since selection of subjects is not controlled by researchers, but by the subjects themselves. In this paper, we characterize RDS procedure under a survival framework, establish a rigorous definition of uniform recruitment and develop statistical estimators and formal tests for recruitment bias when the network of respondents and their alters is fully observed. We apply these tests to a unique RDS study of people who inject drugs in Hartford, CT, USA and find strong evidence to reject the hypothesis of uniform RDS recruitment in this population.

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