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Journal of Official Statistics

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Recruiting an Internet Panel Using Respondent-Driven Sampling

Matthias Schonlau
  • Corresponding author
  • University of Waterloo, Statistics and Act.Sci.200 University Ave, Waterloo, Ontario N2L3G1, Canada.
  • Email:
/ Beverly Weidmer
  • RAND Corporation, Survey Research Group, Los Angeles, California, USA.
  • Email:
/ Arie Kapteyn
  • University of Southern California and RAND Corporation
  • Email:
Published Online: 2014-05-08 | DOI: https://doi.org/10.2478/jos-2014-0018

Abstract

Respondent-driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations when traditional sampling approaches are not feasible (e.g., homeless) or do not work well (e.g., people with HIV). In RDS, seed respondents recruit additional respondents from their network of friends. The recruiting process repeats iteratively, thereby forming long referral chains.

RDS is typically implemented face to face in individual cities. In contrast, we conducted Internet-based RDS in the American Life Panel (ALP), a web survey panel, targeting the general US population. We found that when friends are selected at random, as RDS methodology requires, recruiting chains die out. When self-selecting friends, self-selected friends tend to be older than randomly selected friends but share the same demographic characteristics otherwise.

Using randomized experiments, we also found that respondents list more friends when the respondent’s number of friends is preloaded from an earlier question. The results suggest that with careful selection of parameters, RDS can be used to select population-wide Internet panels and we discuss a number of elements that are critical for success.

Keywords: Web survey; RDS

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About the article

Received: 2013-02-01

Accepted: 2013-11-01

Published Online: 2014-05-08

Published in Print: 2014-06-01



Citation Information: Journal of Official Statistics, ISSN (Online) 2001-7367, DOI: https://doi.org/10.2478/jos-2014-0018. Export Citation

© by Matthias Schonlau. This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY-NC-ND 3.0)

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