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Journal ArticleDOI

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

Cyprian Wejnert, +1 more
- 01 Aug 2008 - 
- Vol. 37, Iss: 1, pp 105-134
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TLDR
Web-based RDS (WebRDS) is found to be highly efficient and effective and methods for testing the validity of assumptions required by RDS estimation are presented.
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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Citations
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Random graphs

TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
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Summary Report of the AAPOR Task Force on Non-probability Sampling

TL;DR: A wide range of non-probability designs exist and are being used in various settings, including case control studies, clinical trials, evaluation research, and more.
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Respondent‐driven sampling: an assessment of current methodology

TL;DR: In this article, the authors evaluate three critical sensitivities of the estimators: to bias induced by the initial sample, to uncontrollable features of respondent behavior, and to the without-replacement structure of sampling.
Posted Content

Respondent-Driven Sampling: An Assessment of Current Methodology

TL;DR: It is indicated that the convenience sample of seeds can induce bias, and the number of sample waves typically used in RDS is likely insufficient for the type of nodal mixing required to obtain the reputed asymptotic unbiasedness.
Journal ArticleDOI

Assessing respondent-driven sampling

TL;DR: Investigating the performance of RDS by simulating sampling from 85 known, network populations finds that RDS is substantially less accurate than generally acknowledged and that reported RDS confidence intervals are misleadingly narrow.
References
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Journal ArticleDOI

Assessment of respondent driven sampling for recruiting female sex workers in two Vietnamese cities: reaching the unseen sex worker.

TL;DR: This study found that RDS was successful at recruiting hidden types of FSWs in Vietnam and that a significant proportion of the FSW population at risk for HIV may not be receiving optimal HIV information and services.
Journal ArticleDOI

Partner naming and forgetting: Recall of network members

TL;DR: In the domain of sex relationships, global estimates of network size, at least over a period of 30 days, are equivalent to estimates from partner naming 92% of the time if anonymous partners are accounted for.
Journal ArticleDOI

Finding the beat: Using respondent-driven sampling to study jazz musicians☆

TL;DR: In this paper, the use of respondent-driven sampling (RDS) was used to identify and survey jazz musicians in four U.S. cities -Detroit, New Orleans, New York and San Francisco.
Journal ArticleDOI

Aids and Social Networks: HIV Prevention Through Network Mobilization

TL;DR: In this article, the authors compared a peer-driven intervention with the standard form of street-based outreach intervention and found that the network intervention outperformed the standard approach with respect to number of people accessed, reductions in self-reported levels of HIV risk behavior and cost.
Journal ArticleDOI

Critical Issues and Further Questions About Respondent-Driven Sampling: Comment on Ramirez-Valles, et al. (2005)

TL;DR: Whether the accompanying paper by Ramirez-Valles et al. fulfills the requirements in terms of the theorems underlying RDS regarding sample recruitment rates, referral patterns, and network sizes is investigated.
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What is referral sampling in research?

Referral sampling, also known as respondent-driven sampling (RDS), is a method in research where participants are recruited through referrals from existing participants.