Respondent-driven Sampling on Directed Networks

Respondent-driven sampling (RDS) is a widely used method for generating chain-referral samples from hidden populations. It is an extension of the snowball sampling method and can, given that some a ...

[1]  Linus Bengtsson,et al.  The sensitivity of respondent‐driven sampling , 2012 .

[2]  Douglas D. Heckathorn,et al.  Simultaneous Recruitment of Drug Users and Men Who Have Sex with Men in the United States and Russia Using Respondent-Driven Sampling: Sampling Methods and Implications , 2009, Journal of Urban Health.

[3]  W. Wallace,et al.  Student culture : social structure and continuity in a liberal arts college , 1966 .

[4]  Colin Cooper,et al.  Algorithms and Models for the Web-Graph , 2004, Lecture Notes in Computer Science.

[5]  M E J Newman.  Assortative mixing in networks. , 2002, Physical review letters.

[6]  Matthew J. Salganik.  Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling , 2006, Journal of Urban Health.

[7]  S. Havlin,et al.  Scaling laws of human interaction activity , 2009, Proceedings of the National Academy of Sciences.

[8]  Xin Lu,et al.  Linked Ego Networks: Improving estimate reliability and validity with respondent-driven sampling , 2012, Soc. Networks.

[9]  Mohsen Malekinejad,et al.  Implementation Challenges to Using Respondent-Driven Sampling Methodology for HIV Biological and Behavioral Surveillance: Field Experiences in International Settings , 2008, AIDS and Behavior.

[10]  Douglas D. Heckathorn,et al.  Respondent-driven sampling : A new approach to the study of hidden populations , 1997 .

[11]  jimi adams,et al.  To tell the truth: Measuring concordance in multiply reported network data , 2007, Soc. Networks.

[12]  B Junge,et al.  Satellite exchange in the Baltimore Needle Exchange Program. , 1998, Public health reports.

[13]  Krista Gile.  Improved Inference for Respondent-Driven Sampling Data With Application to HIV Prevalence Estimation , 2010, 1006.4837.

[14]  A. Barabasi,et al.  Percolation in directed scale-free networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  P. Biernacki,et al.  TARGETED SAMPLING: OPTIONS FOR THE STUDY OF HIDDEN POPULATIONS , 1989 .

[16]  Erik M Volz,et al.  Using Respondent-Driven Sampling in a Hidden Population at Risk of HIV Infection: Who Do HIV-Positive Recruiters Recruit? , 2009, Sexually transmitted diseases.

[17]  Erik M. Volz,et al.  Probability based estimation theory for respondent driven sampling , 2008 .

[18]  Karl W Broman,et al.  Multiperson Use of Syringes Among Injection Drug Users in a Needle Exchange Program: A Gene-Based Molecular Epidemiologic Analysis , 2006, Journal of acquired immune deficiency syndromes.

[19]  Bonnie H. Erickson,et al.  Some Problems of Inference from Chain Data , 1979 .

[20]  W. C. Carter,et al.  Detecting measurement bias in respondent reports of personal networks , 2002, Soc. Networks.

[21]  Amber Tomas,et al.  The effect of differential recruitment, non-response and non-recruitment on estimators for respondent-driven sampling , 2010, 1012.4122.

[22]  Matthew J. Salganik,et al.  Respondent‐driven sampling as Markov chain Monte Carlo , 2009, Statistics in medicine.

[23]  Cyprian Wejnert,et al.  Web-Based Network Sampling , 2008 .

[24]  Douglas D. Heckathorn,et al.  Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hi , 2002 .

[25]  A. Shapiro.  Monte Carlo Sampling Methods , 2003 .

[26]  Anatol Rapoport,et al.  A probabilistic approach to networks , 1979 .

[27]  Douglas D. Heckathorn,et al.  Effectiveness of Respondent–Driven Sampling for Recruiting Drug Users in New York City: Findings from a Pilot Study , 2007, Journal of Urban Health.

[28]  Chareen Snelson,et al.  Sampling the Web: The Development of a Custom Search Tool for Research , 2006 .

[29]  Mohsen Malekinejad,et al.  Using Respondent-Driven Sampling Methodology for HIV Biological and Behavioral Surveillance in International Settings: A Systematic Review , 2008, AIDS and Behavior.

[30]  A. Fisher,et al.  The Theory of critical phenomena , 1992 .

[31]  E. Deaux,et al.  Key Informant Versus Self-Report Estimates of Health-Risk Behavior , 1985 .

[32]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[33]  Edward T. O'Neill,et al.  A Methodology for Sampling the World Wide Web , 2001 .

[34]  Cyprian Wejnert,et al.  3. An Empirical Test of Respondent-Driven Sampling: Point Estimates, Variance, Degree Measures, and Out-of-Equilibrium Data , 2009, Sociological methodology.

[35]  J. D. de Wit,et al.  Use of respondent-driven sampling to enhance understanding of injecting networks: a study of people who inject drugs in Sydney, Australia. , 2011, The International journal on drug policy.

[36]  Matthew J. Salganik,et al.  5. Sampling and Estimation in Hidden Populations Using Respondent-Driven Sampling , 2004 .

[37]  Dana L Haynie,et al.  Friendship Networks of Mobile Adolescents , 2004 .

[38]  I. Sokolov,et al.  Reshuffling scale-free networks: from random to assortative. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[39]  Mark S Handcock,et al.  7. Respondent-Driven Sampling: An Assessment of Current Methodology , 2009, Sociological methodology.

[40]  Minas Gjoka,et al.  Walking in Facebook: A Case Study of Unbiased Sampling of OSNs , 2010, 2010 Proceedings IEEE INFOCOM.

[41]  Min Xu,et al.  Trends in Prevalence of HIV, Syphilis, Hepatitis C, Hepatitis B, and Sexual Risk Behavior Among Men Who Have Sex With Men: Results of 3 Consecutive Respondent-Driven Sampling Surveys in Beijing, 2004 Through 2006 , 2007, Journal of acquired immune deficiency syndromes.

[42]  Matthew J. Salganik,et al.  Assessing respondent-driven sampling , 2010, Proceedings of the National Academy of Sciences.

[43]  W. K. Hastings,et al.  Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .

[44]  Martina Morris,et al.  Concurrent Partnerships and Trans-mission Dynamics in Networks , 1995 .

[45]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .