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Web-Based Network Sampling: Efficiency and Efficacy of Respondent-Driven Sampling for Online Research

Cornell University

^* To whom correspondence should be addressed. E-mail: cw79{at}cornell.edu.

	Abstract

This study tests the feasibility, effectiveness, and efficiency of respondent-driven sampling (RDS) as a Web-based sampling method. Web-based RDS (WebRDS) is found to be highly efficient and effective. The online nature of WebRDS allows referral chains to progress very quickly, such that studies with large samples can be expected to proceed up to 20 times faster than with traditional sampling methods. Additionally, the unhidden nature of the study population allows comparison of RDS estimators to institutional data. Results indicate that RDS estimates are reasonable but not precise. This is likely due to bias associated with the random recruitment assumption and small sample size of the study. Finally, this article presents methods for testing the validity of assumptions required by RDS estimation.

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