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The sensitivity of respondent-driven sampling
Stockholm University, Faculty of Social Sciences, Department of Sociology.
Stockholm University, Faculty of Science, Department of Mathematics.
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2012 (English)In: Journal of the Royal Statistical Society: Series A (Statistics in Society), ISSN 0964-1998, E-ISSN 1467-985X, Vol. 175, no 1, 191-216 p.Article in journal (Refereed) Published
Abstract [en]

Researchers in many scientific fields make inferences from individuals to larger groups. For many groups, however, there is no list of members from which to draw a random sample. Respondent-driven sampling (RDS) is a relatively new sampling methodology that circumvents this difficulty by using the social networks of the groups under study. The RDS method has been shown to provide unbiased estimates of population proportions given certain conditions. The method is now widely used in human immunodeficiency virus related studies among high risk populations globally. We test the RDS methodology by simulating RDS studies on the social networks of a large Lesbian, gay, bisexual and transgender Web community. The robustness of the RDS method is tested by violating, one by one, the conditions under which the method provides unbiased estimates. Simulations indicate that the bias is large if networks are directed or respondents choose to invite people on the basis of characteristics that are correlated with the study outcomes. The bias and variance increase if participants invite close as opposed to more distant friends whereas sampling in denser networks sharply reduces variance. However, the RDS method shows strong resistance to sampling without replacement, low response rates and certain errors in the participants reporting of their network sizes, as well as the selection criteria of seeds. The effects of network structure and the number of seeds and coupons are also discussed.

Place, publisher, year, edition, pages
2012. Vol. 175, no 1, 191-216 p.
Keyword [en]
Directed network, Hidden population, Network, Respondent-driven sampling, Sampling, Sensitivity
National Category
Probability Theory and Statistics Sociology
URN: urn:nbn:se:su:diva-76762DOI: 10.1111/j.1467-985X.2011.00711.xISI: 000299154500009OAI: diva2:527126


Available from: 2012-05-16 Created: 2012-05-16 Last updated: 2013-04-22Bibliographically approved

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Lu, XinBritton, TomLiljeros, Fredrik
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