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Exploring Mechanisms of Recruitment and Recruitment Cooperation in Respondent Driven Sampling

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  • Lee Sunghee
  • Ong Ai Rene
  • Elliott Michael

    (Institute for Social Research, University of Michigan, 426 Thompson St., Ann Arbor, MI 48104, U.S.A.)

Abstract

Respondent driven sampling (RDS) is a sampling method designed for hard-to-sample groups with strong social ties. RDS starts with a small number of arbitrarily selected participants (“seeds”). Seeds are issued recruitment coupons, which are used to recruit from their social networks. Waves of recruitment and data collection continue until reaching a sufficient sample size. Under the assumptions of random recruitment, with-replacement sampling, and a sufficient number of waves, the probability of selection for each participant converges to be proportional to their network size. With recruitment noncooperation, however, recruitment can end abruptly, causing operational difficulties with unstable sample sizes. Noncooperation may void the recruitment Markovian assumptions, leading to selection bias. Here, we consider two RDS studies: one targeting Korean immigrants in Los Angeles and in Michigan; and another study targeting persons who inject drugs in Southeast Michigan. We explore predictors of coupon redemption, associations between recruiter and recruits, and details within recruitment dynamics. While no consistent predictors of noncooperation were found, there was evidence that coupon redemption of targeted recruits was more common among those who shared social bonds with their recruiters, suggesting that noncooperation is more likely to be a feature of recruits not cooperating, rather than recruiters failing to distribute coupons.

Suggested Citation

  • Lee Sunghee & Ong Ai Rene & Elliott Michael, 2020. "Exploring Mechanisms of Recruitment and Recruitment Cooperation in Respondent Driven Sampling," Journal of Official Statistics, Sciendo, vol. 36(2), pages 339-360, June.
  • Handle: RePEc:vrs:offsta:v:36:y:2020:i:2:p:339-360:n:7
    DOI: 10.2478/jos-2020-0018
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    References listed on IDEAS

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    1. Xin Lu & Linus Bengtsson & Tom Britton & Martin Camitz & Beom Jun Kim & Anna Thorson & Fredrik Liljeros, 2012. "The sensitivity of respondent‐driven sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(1), pages 191-216, January.
    2. Krista J. Gile & Lisa G. Johnston & Matthew J. Salganik, 2015. "Diagnostics for respondent-driven sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 241-269, January.
    3. Nicky McCreesh & Andrew Copas & Janet Seeley & Lisa G Johnston & Pam Sonnenberg & Richard J Hayes & Simon D W Frost & Richard G White, 2013. "Respondent Driven Sampling: Determinants of Recruitment and a Method to Improve Point Estimation," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-9, October.
    4. Krista J. Gile & Mark S. Handcock, 2015. "Network model-assisted inference from respondent-driven sampling data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 619-639, June.
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