|matthew salganik :: respondent-driven sampling|
Respondent-driven sampling is a form of snowball sampling which allows researchers to make estimates about hidden population such as the three groups at highest risk for HIV/AIDS: injection drug users, sex workers, and men who have sex with men. It can be used to answer questions such as "What percentage of drug injectors in New York City share needles?" or "What percentage of sex workers in Atlanta have HIV/AIDS?" Respondent-driven sampling is currently be used by the U.S. Center for Disease Control and Prevention (CDC) and other international health organizations; a 2008 review article by Malekinejad et al. identified more than 120 respondent-driven sampling studies in 20 countries.
A respondent-driven sample is collected via a snowballing design, where current subjects recruit their friends to be future subjects. Because subjects are not selected via simple random sampling, care must be taken when making estimates from this type of sample. It was shown that if certain conditions are met and if the appropriate estimation procedures are used, then prevalence estimates from this type of sample are unbiased (Salganik and Heckathorn, 2004; Volz and Heckathorn, 2008). However, if the appropriate conditions are not met, the estimates can be biased (Gile and Hancock, 2010). Further, even if the appropriate conditions are met, the estimates from respondent-driven sampling can have very high variance due to "bottlenecks" in the underlying network structure of the hidden population (Goel and Salganik, 2009; Goel and Salganik, 2010).
My papers about respondent-driven sampling:White, R.G., Hakim, A.J., Salganik, M.J., Spiller, M.W., Johnston, L.G., Kerr, L.R.F.S., Kendall, C., Drake, A., Wilson, D., Orroth, K., Egger, M., Hladik, W.W. 2015. "Strengthening the Reporting of Observational Studies in Epidemiology for Respondent-Driven Sampling Studies: STROBE-RDS Statement." Journal of Clinical Epidemiology, in press.
Gile, Krista, Johnston, Lisa, and Matthew J. Salganik. 2015. "Diagnostics for respondent-driven sampling." Journal of the Royal Statistical Society, Series A (Statistics and Society), 178:241-269.
Matthew J. Salganik. 2012. "Commentary: Respondent-driven sampling in the real world." Epidemiology, 23:148-150.
Sharad Goel and Matthew J. Salganik. 2010. "Assessing respondent-driven sampling." Proceedings of the National Academy of Sciences, 107:6743-6747.
Sharad Goel and Matthew J. Salganik. 2009. "Respondent-driven sampling as Markov chain Monte Carlo." Statistics in Medicine, 28:2202-2229.
Matthew J. Salganik. 2006. "Variance estimation, design effects, and sample size calculations for respondent-driven sampling." Journal of Urban Health, 83:98-111.
Matthew J. Salganik and Douglas D. Heckathorn. 2004. "Sampling and estimation in hidden populations using respondent-drive sampling." Sociological Methodology, 34:193-239.
Other papers about respondent-driven sampling:Krista Gile and Mark S. Handcock. 2010. "Respondent-driven sampling: An assessment of current methodology." Sociological Methodology, 40:285–327.
Erik Volz and Douglas D. Heckathorn. 2008. "Probability based estimation theory for Respondent Driven Sampling." Journal of Official Statistics, 24:1.
Special issue of Journal of Urban Health all about respondent-driven sampling
Douglas D. Heckathorn. 2002. "Respondent-driven sampling II: Deriving valid population estimates from chain-referral samples of hidden populations." Social Problems, 49:11-34.
Douglas D. Heckathorn. 1997 "Respondent-driven sampling: A new approach to the study of hidden populations." Social Problems, 44:174-199.
Other information about respondent-driven sampling:Lisa Johnston has lots of useful respondent-driven sampling materials on her website.
Respondent-driven sampling mailing list:I maintain a respondent-driven sampling email list that currently has about 250 members. This is a venue for researchers to share ideas and questions.