IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0078402.html
   My bibliography  Save this article

Respondent Driven Sampling: Determinants of Recruitment and a Method to Improve Point Estimation

Author

Listed:
  • Nicky McCreesh
  • Andrew Copas
  • Janet Seeley
  • Lisa G Johnston
  • Pam Sonnenberg
  • Richard J Hayes
  • Simon D W Frost
  • Richard G White

Abstract

Introduction: Respondent-driven sampling (RDS) is a variant of a link-tracing design intended for generating unbiased estimates of the composition of hidden populations that typically involves giving participants several coupons to recruit their peers into the study. RDS may generate biased estimates if coupons are distributed non-randomly or if potential recruits present for interview non-randomly. We explore if biases detected in an RDS study were due to either of these mechanisms, and propose and apply weights to reduce bias due to non-random presentation for interview. Methods: Using data from the total population, and the population to whom recruiters offered their coupons, we explored how age and socioeconomic status were associated with being offered a coupon, and, if offered a coupon, with presenting for interview. Population proportions were estimated by weighting by the assumed inverse probabilities of being offered a coupon (as in existing RDS methods), and also of presentation for interview if offered a coupon by age and socioeconomic status group. Results: Younger men were under-recruited primarily because they were less likely to be offered coupons. The under-recruitment of higher socioeconomic status men was due in part to them being less likely to present for interview. Consistent with these findings, weighting for non-random presentation for interview by age and socioeconomic status group greatly improved the estimate of the proportion of men in the lowest socioeconomic group, reducing the root-mean-squared error of RDS estimates of socioeconomic status by 38%, but had little effect on estimates for age. The weighting also improved estimates for tribe and religion (reducing root-mean-squared-errors by 19–29%), but had little effect for sexual activity or HIV status. Conclusions: Data collected from recruiters on the characteristics of men to whom they offered coupons may be used to reduce bias in RDS studies. Further evaluation of this new method is required.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0078402
    DOI: 10.1371/journal.pone.0078402
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0078402
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0078402&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0078402?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gile, Krista J., 2011. "Improved Inference for Respondent-Driven Sampling Data With Application to HIV Prevalence Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 135-146.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ian E. Fellows & Mark S. Handcock, 2023. "Modeling of networked populations when data is sampled or missing," METRON, Springer;Sapienza Università di Roma, vol. 81(1), pages 21-35, April.
    2. Fatemi, Samira & Salehi, Mostafa & Veisi, Hadi & Jalili, Mahdi, 2018. "A fuzzy logic based estimator for respondent driven sampling of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 42-51.
    3. Chien-Min Huang & F. Jay Breidt, 2023. "A dual-frame approach for estimation with respondent-driven samples," METRON, Springer;Sapienza Università di Roma, vol. 81(1), pages 65-81, April.
    4. Lisa Avery & Alison Macpherson & Sarah Flicker & Michael Rotondi, 2021. "A review of reported network degree and recruitment characteristics in respondent driven sampling implications for applied researchers and methodologists," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-19, April.
    5. Dongah Kim & Krista J. Gile & Honoria Guarino & Pedro Mateu‐Gelabert, 2021. "Inferring bivariate association from respondent‐driven sampling data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 415-433, March.
    6. Florence Samkange-Zeeb & Ronja Foraita & Stefan Rach & Tilman Brand, 2019. "Feasibility of using respondent-driven sampling to recruit participants in superdiverse neighbourhoods for a general health survey," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 64(3), pages 451-459, April.
    7. Malmros Jens & Masuda Naoki & Britton Tom, 2016. "Random Walks on Directed Networks: Inference and Respondent-Driven Sampling," Journal of Official Statistics, Sciendo, vol. 32(2), pages 433-459, June.
    8. Yakir Berchenko & Jonathan D. Rosenblatt & Simon D. W. Frost, 2017. "Modeling and analyzing respondent‐driven sampling as a counting process," Biometrics, The International Biometric Society, vol. 73(4), pages 1189-1198, December.
    9. Merli, M. Giovanna & Moody, James & Smith, Jeffrey & Li, Jing & Weir, Sharon & Chen, Xiangsheng, 2015. "Challenges to recruiting population representative samples of female sex workers in China using Respondent Driven Sampling," Social Science & Medicine, Elsevier, vol. 125(C), pages 79-93.
    10. Barash Vladimir D. & Cameron Christopher J. & Spiller Michael W. & Heckathorn Douglas D., 2016. "Respondent-Driven Sampling – Testing Assumptions: Sampling with Replacement," Journal of Official Statistics, Sciendo, vol. 32(1), pages 29-73, March.
    11. Aronow, Peter M. & Crawford, Forrest W., 2015. "Nonparametric identification for respondent-driven sampling," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 100-102.
    12. Ali Mirzazadeh & Yea-Hung Chen & Jess Lin & Katie Burk & Erin C Wilson & Desmond Miller & Danielle Veloso & Willi McFarland & Meghan D Morris, 2021. "Progress toward closing gaps in the hepatitis C virus cascade of care for people who inject drugs in San Francisco," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-11, April.
    13. Thespina J. Yamanis & M. Giovanna Merli & William Whipple Neely & Felicia Feng Tian & James Moody & Xiaowen Tu & Ersheng Gao, 2013. "An Empirical Analysis of the Impact of Recruitment Patterns on RDS Estimates among a Socially Ordered Population of Female Sex Workers in China," Sociological Methods & Research, , vol. 42(3), pages 392-425, August.
    14. Mart L Stein & Vincent Buskens & Peter G M van der Heijden & Jim E van Steenbergen & Albert Wong & Martin C J Bootsma & Mirjam E E Kretzschmar, 2018. "A stochastic simulation model to study respondent-driven recruitment," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-19, November.
    15. Hernández, Hugo & Quiroz, Gabriel & Zambrano, Omar & Zanoni, Wladimir, 2023. "Measuring Labor Market Discrimination against LGTBQ+ in the Case of Ecuador: A Field Experiment," IDB Publications (Working Papers) 12977, Inter-American Development Bank.
    16. Zanoni, Wladimir & Fabregas, Raissa, 2024. "The Migrant Penalty in Latin America: Experimental Evidence from Job Recruiters," IDB Publications (Working Papers) 13804, Inter-American Development Bank.
    17. Mark S. Handcock & Krista J. Gile & Corinne M. Mar, 2015. "Estimating the size of populations at high risk for HIV using respondent-driven sampling data," Biometrics, The International Biometric Society, vol. 71(1), pages 258-266, March.
    18. Schonlau, Matthias & Liebau, Elisabeth, 2012. "Respondent-Driven Sampling," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12(1), pages 72-93.
    19. Lee Sunghee & Suzer-Gurtekin Tuba & Wagner James & Valliant Richard, 2017. "Total Survey Error and Respondent Driven Sampling: Focus on Nonresponse and Measurement Errors in the Recruitment Process and the Network Size Reports and Implications for Inferences," Journal of Official Statistics, Sciendo, vol. 33(2), pages 335-366, June.
    20. Matthias Schonlau & Elisabeth Liebau, 2012. "Respondent-driven sampling," Stata Journal, StataCorp LP, vol. 12(1), pages 72-93, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0078402. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.