Hidden populations are, by definition, hard-to-reach, but are often of great interest in scientific studies;examples of such populations include the homeless, injection drug users, and men who have sex with men. Respondent- driven sampling (RDS) involves peers recruiting their peers (usually friends and acquaintances) through the use of a small number of uniquely-numbered coupons per participant. RDS employs a 'double incentive'system, where individuals are compensated both for participating in the study and for successfully recruiting other eligible participants. Not only does RDS allow members of hidden populations to be recruited efficiently in this manner, it also provides information on mixing between different subpopulations (otherwise known as 'homophily') and on network sizes of individuals, both important factors underlying the structure of social networks. Although RDS is currently being used in a large number of studies around the world, methodology to analyze the data being generated by these studies needs to be developed and validated. Our application has three overarching aims;to develop statistical models to analyze homophily and network size, two important features of the structure of social networks;to develop weighting schemes which correct for the biased nature of RDS samples, to allow standard statistical approaches to be applied;and to develop a simulation environment to investigate the statistical properties of our approaches and the robustness of parameter estimates to model assumptions. Our application melds state-of-the-art statistical inference and computational modeling in order to address long-standing questions in sociology. Respondent-driven sampling (RDS) is a technique to sample individuals from 'hidden'populations, such as the homeless, injection drug users, and men who have sex with men, which involves peers recruiting their peers. Not only does RDS allow members of hidden populations to be recruited efficiently in this manner, it also provides information on mixing between different subpopulations (otherwise known as 'homophily') and on network sizes of individuals, both important factors underlying the structure of social networks. Our application has three overarching aims;to develop statistical models to analyze homophily and network size, two important features of the structure of social networks;to develop weighting schemes which correct for the biased nature of RDS samples, to allow standard statistical approaches to be applied;and to develop a simulation environment to investigate the statistical properties of our approaches and the robustness of parameter estimates to model assumptions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Exploratory/Developmental Grants (R21)
Project #
7R21NR010961-02
Application #
7652400
Study Section
Special Emphasis Panel (ZDA1-GXM-A (27))
Program Officer
Hosseini, Jeanette M
Project Start
2008-07-10
Project End
2013-04-30
Budget Start
2009-05-07
Budget End
2011-04-30
Support Year
2
Fiscal Year
2009
Total Cost
$225,261
Indirect Cost
Name
Cornell University
Department
Social Sciences
Type
Schools of Arts and Sciences
DUNS #
872612445
City
Ithaca
State
NY
Country
United States
Zip Code
14850
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Wagner, Glenn J; Tohme, Johnny; Hoover, Matthew et al. (2014) HIV prevalence and demographic determinants of unprotected anal sex and HIV testing among men who have sex with men in Beirut, Lebanon. Arch Sex Behav 43:779-88
McCreesh, Nicky; Copas, Andrew; Seeley, Janet et al. (2013) Respondent driven sampling: determinants of recruitment and a method to improve point estimation. PLoS One 8:e78402
Havens, Jennifer R; Lofwall, Michelle R; Frost, Simon D W et al. (2013) Individual and network factors associated with prevalent hepatitis C infection among rural Appalachian injection drug users. Am J Public Health 103:e44-52
White, Richard G; Lansky, Amy; Goel, Sharad et al. (2012) Respondent driven sampling--where we are and where should we be going? Sex Transm Infect 88:397-9
McCreesh, Nicky; Frost, Simon D W; Seeley, Janet et al. (2012) Evaluation of respondent-driven sampling. Epidemiology 23:138-47
McCreesh, Nicky; Johnston, Lisa G; Copas, Andrew et al. (2011) Evaluation of the role of location and distance in recruitment in respondent-driven sampling. Int J Health Geogr 10:56
Berchenko, Yakir; Frost, Simon D W (2011) Capture-recapture methods and respondent-driven sampling: their potential and limitations. Sex Transm Infect 87:267-8
Heckathorn, Douglas D (2011) SNOWBALL VERSUS RESPONDENT-DRIVEN SAMPLING. Sociol Methodol 41:355-366
Wejnert, Cyprian (2010) SOCIAL NETWORK ANALYSIS WITH RESPONDENT-DRIVEN SAMPLING DATA: A STUDY OF RACIAL INTEGRATION ON CAMPUS. Soc Networks 32:112-124

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