Diagnostics for respondent-driven sampling
Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for human immunodeficiency virus or acquired immune deficiency syndrome. Data are collected through a peer referral process over social networks. RDS has...
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| Published in | Journal of the Royal Statistical Society. Series A, Statistics in society Vol. 178; no. 1; pp. 241 - 269 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Blackwell Publishing Ltd
01.01.2015
John Wiley & Sons Ltd Oxford University Press |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for human immunodeficiency virus or acquired immune deficiency syndrome. Data are collected through a peer referral process over social networks. RDS has proven practical for data collection in many difficult settings and has been adopted by leading public health organizations around the world. Unfortunately, inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and not fully observable. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to understand their RDS data better and encourage future statistical research on RDS sampling and inference. |
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| AbstractList | Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for HIV. Data are collected through peer-referral over social networks. RDS has proven practical for data collection in many difficult settings and is widely used. Inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and partially unobserved. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to better understand their data and encourage future statistical research on RDS. Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for human immunodeficiency virus or acquired immune deficiency syndrome. Data are collected through a peer referral process over social networks. RDS has proven practical for data collection in many difficult settings and has been adopted by leading public health organizations around the world. Unfortunately, inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and not fully observable. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to understand their RDS data better and encourage future statistical research on RDS sampling and inference. Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for human immunodeficiency virus or acquired immune deficiency syndrome. Data are collected through a peer referral process over social networks. RDS has proven practical for data collection in many difficult settings and has been adopted by leading public health organizations around the world. Unfortunately, inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and not fully observable. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to understand their RDS data better and encourage future statistical research on RDS sampling and inference. Reprinted by permission of Blackwell Publishers Summary Respondent‐driven sampling (RDS) is a widely used method for sampling from hard‐to‐reach human populations, especially populations at higher risk for human immunodeficiency virus or acquired immune deficiency syndrome. Data are collected through a peer referral process over social networks. RDS has proven practical for data collection in many difficult settings and has been adopted by leading public health organizations around the world. Unfortunately, inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and not fully observable. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to understand their RDS data better and encourage future statistical research on RDS sampling and inference. |
| Author | Johnston, Lisa G. Salganik, Matthew J. Gile, Krista J. |
| Author_xml | – sequence: 1 givenname: Krista J. surname: Gile fullname: Gile, Krista J. email: gile@math.umass.edu organization: University of Massachusetts, Amherst, USA – sequence: 2 givenname: Lisa G. surname: Johnston fullname: Johnston, Lisa G. organization: Tulane University, New Orleans – sequence: 3 givenname: Matthew J. surname: Salganik fullname: Salganik, Matthew J. organization: Microsoft Research, New York |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27226702$$D View this record in MEDLINE/PubMed |
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| Publisher | Blackwell Publishing Ltd John Wiley & Sons Ltd Oxford University Press |
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| References | Wejnert, C. (2009) An empirical test of respondent-driven sampling: point estimates, variance, degree measures, and out-of-equilibrium data. Sociol. Methodol., 39, 73-116. Frost, S. D., Brouwer, K. C., Firestone Cruz, M. A., Ramos, R., Ramos, M. E., Lozada, R. M., Magis-Rodriguez, C. and Strathdee, S. A. (2006) Respondent-driven sampling of injection drug users in two US-Mexico border cities: recruitment dynamics and impact on estimates of HIV and Syphilis prevalence. J. Urb. Hlth, 83, 83-97. Iguchi, M. Y., Ober, A. J., Berry, S. H., Fain, T., Heckathorn, D. D., Gorbach, P. M., Heimer, R., Kozlov, A., Ouellet, L. J., Shoptaw, S. and Zule, W. A. (2009) 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. J. Urb. Hlth, 86, suppl. 1, 5-31. Volz, E. and Heckathorn, D. D. (2008) Probability based estimation theory for respondent driven sampling. J. Off. Statist., 24, 79-97. Wang, J., Carlson, R. G., Falck, R. S., Siegal, H. A., Rahman, A. and Li, L. (2005) Respondent-driven sampling to recruit MDMA users: a methodological assessment. Drug Alc. Depend., 78, 147-157. Stormer, A., Tun, W., Guli, L., Harxhi, A., Bodanovskaia, Z., Yakovleva, A., Rusakova, M., Levina, O., Bani, R., Rjepaj, K. and Bino, S. (2006) An analysis of respondent driven sampling with injection drug users (IDU) in Albania and the Russian Federation. J. Urb. Hlth, 83, 73-82. Lansky, A., Drake, A., Wejnert, C., Pham, H., Cribbin, M. and Heckathorn, D. D. (2012) Assessing the assumptions of respondent-driven sampling in the National HIV Behavioral Surveillance System among injecting drug users. Open AIDS J., 6, 77-82. Broadhead, R. S. (2008) Notes on a cautionary (tall) tale about respondent-driven sampling: a critique of Scott's ethnography. Int. J. Drug Poly, 19, 235-237. Wejnert, C., Pham, H., Krishna, N., Le, B. and DiNenno, E. (2012) Estimating design effect and calculating sample size for respondent-driven sampling studies of injection drug users in the United States. AIDS Behav., 16, 797-806. Marsden, P. V. (1990) Network data and measurement. A. Rev. Sociol., 16, 435-463. McCreesh, N., Frost, S. D. W., Seeley, J., Katongole, J., Tarsh, M. N., Ndunguse, R., Jichi, F., Lunel, N. L., Maher, D., Johnston, L. G., Sonnenberg, P., Copas, A. J., Hayes, R. J. and White, R. G. (2012) Evaluation of respondent-driven sampling. Epidemiology, 23, 138-147. Gelman, A. and Rubin, D. B. (1992) Inference from iterative simulation using multiple sequences. Statist. Sci., 7, 457-472. Heckathorn, D. D. (1997) Respondent-driven sampling: a new approach to the study of hidden populations. Socl Prob., 44, 174-199. Nesterko, S. and Blitzstein, J. (2014) Bias-variance and breadth-depth tradeoffs in respondent-driven sampling. J. Statist. Computn Simuln, to be published. Johnston, L. G., Chen, Y.-H., Silva-Santisteban, A. and Raymond, H. F. (2013) An empirical examination of respondent driven sampling design effects among HIV risk groups from studies conducted around the world. AIDS Behav., 17, 2202-2210. Ramirez-Valles, J., Heckathorn, D. D., Vázquez, R., Diaz, R. M. and Campbell, R. T. (2005a) From networks to populations: the development and application of respondent-driven sampling among IDUs and Latino gay men. AIDS Behav., 9, 387-402. Barbosa Júnior, A., Pati Pascom, A. R., Szwarcwald, C. L., Kendall, C. and McFarland, W. (2011) Transfer of sampling methods for studies on most-at-risk populations (MARPs) in Brazil. Cad. Sde Publ., 27, suppl. S1, S36-S44. Johnston, L. G., Caballero, T., Dolores, Y. and Values, H. M. (2013) HIV, Hepatitis B/C and Syphilis prevalence and risk behaviors among gay/trans/men who have sex with men, Dominican Republic. Int. J. STD AIDS, 24313-321. Lansky, A., Abdul-Quader, A. S., Cribbin, M., Hall, T., Finlayson, T. J., Garfein, R. S., Lin, L. S. and Sullivan, P. S. (2007) Developing an HIV behavioral surveillance system for injecting drug users: the National HIV Behavioral Surveillance System. Publ. Hlth Rep., 122, suppl. 1, 48-55. Lu, X. (2013) Linked ego networks: improving estimate reliability and validity with respondent-driven sampling. Socl Netwrks, 35, 669-685. Ouellet, L. J. (2008) Cautionary comments on an ethnographic tale gone wrong. Int. J. Drug Poly, 19, 238-240. Bernard, H. R., Hallett, T., Iovita, A., Johnsen, E. C., Lyerla, R., McCarty, C., Mahy, M., Salganik, M. J., Saliuk, T., Scutelniciuc, O., Shelley, G. A., Sirinirund, P., Weir, S. and Stroup, D. F. (2010) Counting hard-to-count populations: the network scale-up method for public health. Sexlly Transmttd Infect., 86, suppl. 2, ii11-ii15. Scott, G. (2008) "They got their program, and I got mine": a cautionary tale concerning the ethical implications of using respondent-driven sampling to study injection drug users. Int. J. Drug Poly, 19, 42-51. Bengtsson, L. and Thorson, A. (2010) Global HIV surveillance among MSM: is risk behavior seriously underestimated? AIDS, 24, 2301-2303. Brewer, D. D. (2000) Forgetting in the recall-based elicitation of personal and social networks. Socl Netwrks, 22, 29-43. Lu, X., Bengtsson, L., Britton, T., Camitz, M., Kim, B. J., Thorson, A. and Liljeros, F. (2012) The sensitivity of respondent-driven sampling. J. R. Statist. Soc. A, 175, 191-216. Rudolph, A. E., Fuller, C. M. and Latkin, C. (2013) The importance of measuring and accounting for potential biases in respondent-driven samples. AIDS Behav., 17, 2244-2252. Wejnert, C. and Heckathorn, D. D. (2008) Web-based network sampling efficiency and efficacy of respondent-driven sampling for online research. Sociol. Meth. Res., 37, 105-134. Bernard, H. R., Killworth, P., Kronenfeld, D. and Sailer, L. (1984) The problem of informant accuracy: the validity of retrospective data. A. Rev. Anthrop., 13, 495-517. Johnston, L. G., Prybylski, D., Raymond, H. F., Mirzazadeh, A., Manopaiboon, C. and McFarland, W. (2013) Incorporating the service multiplier method in respondent-driven sampling surveys to estimate the size of hidden and hard-to-reach populations. Sexlly Transmttd Dis., 40, 304-310. Johnston, L. G., Khanam, R., Reza, M., Khan, S. I., Banu, S., Alam, M. S., Rahman, M. and Azim, T. (2008) The effectiveness of respondent driven sampling for recruiting males who have sex with males in Dhaka, Bangladesh. AIDS Behav., 12, 294-304. Goel, S. and Salganik, M. J. (2009) Respondent-driven sampling as Markov chain Monte Carlo. Statist. Med., 28, 2202-2229. McCreesh, N., Tarsh, M. N., Seeley, J., Katongole, J. and White, R. G. (2013) Community understanding of respondent-driven sampling in a medical research setting in Uganda: importance for the use of RDS for public health research. Int. J. Socl Res. Methodol., 16, 269-284. Salganik, M. J., Fazito, D., Bertoni, N., Abdo, A. H., Mello, M. B. and Bastos, F. I. (2011) Assessing network scale-up estimates for groups most at risk of HIV/AIDS: evidence from a multiple-method study of heavy drug users in Curitiba, Brazil. Am. J. Epidem., 174, 1190-1196. Salganik, M. J. and Heckathorn, D. D. (2004) Sampling and estimation in hidden populations using respondent-driven sampling. Sociol. Methodol., 34, 193-240. Szwarcwald, C. L., de Souza Júnior, P. R. B., Damacena, G. N., Junior, A. B.and Kendall, C. (2011) Analysis of data collected by RDS among sex workers in 10 Brazilian cities, 2009: estimation of the prevalence of HIV, variance, and design effect. J. Acq. Immune Defic. Synd., 57, suppl., S129-S135. Rudolph, A. E., Crawford, N. D., Latkin, C., Heimer, R., Benjamin, E. O., Jones, K. C. and Fuller, C. M. (2011) Subpopulations of illicit drug users reached by targeted street outreach and respondent-driven sampling strategies: implications for research and public health practice. Ann. Epidem., 21, 280-289. Malekinejad, M., Johnston, L. G., Kendall, C., Kerr, L. R., Rifkin, M. R. and Rutherford, G. W. (2008) Using respondent-driven sampling methodology for HIV biological and behavioral surveillance in international settings: a systematic review. AIDS Behav., 12, 105-130. Kerr, L. R. F. S., Kendall, C., Pontes, M. K., Werneck, G. L., McFarland, W., Mello, M. B., Martins, T. A. and Macena, R. H. M. (2011) Selective participation in a RDS survey among MSM in Ceara, Brazil: a qualitative and quantitative assessment. J. Bras. Doenc. Sexmnte Transmiss., 23, 126-133. Liu, H., Li, J., Ha, T. and Li, J. (2012) Assessment of random recruitment assumption in respondent-driven sampling in egocentric network data. Socl Netwrkng, 1, 13-21. Burt, R. D. and Thiede, H. (2012) Evaluating consistency in repeat surveys of injection drug users recruited by respondent-driven sampling in the Seattle area: results from the NHBS-IDU1 and NHBS-IDU2 surveys. Ann. Epidem., 22, 354-363. Gile, K. J. (2011) Improved inference for respondent-driven sampling data with application to HIV prevalence estimation. J. Am. Statist. Ass., 106, 135-146. Salganik, M. J. (2012) Commentary: Respondent-driven sampling in the real world. Epidemiology, 23, 148-150. Goel, S. and Salganik, M. J. (2010) Assessing respondent-driven sampling. Proc. Natn. Acad. Sci. USA, 107, 6743-6747. White, R. G., Lansky, A., Goel, S., Wilson, D., Hladik, W., Hakim, A. and Frost, S. D. (2012) Respondent driven sampling-where we are and where should we be going? Sexlly Transmttd Infectns, 88, 397-399. Heckathorn, D. D. (2002) Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hidden populations. Socl Prob., 49, 11-34. Heckathorn, D., Semaan, S., Broadhead, R. and Hughes, J. (2002) Extensions of respondent-driven sampling: a new approach to the study of injection drug users aged 18-25. AIDS Behav., 6, 55-67. Magnani, R., Sabin, K., Saidel, T. and Heckathorn, D. (2005) Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS, 19, suppl., S67-S72. Tomas, A. and Gile, K. J. (2011) The effect of differential recruitment, non-response and non-recruitment on estimators for respondent-driven sam 2009; 86 2010; 107 1997; 44 1990; 16 2013; 24 2008; 37 2005b; 9 2011; 57 2012; 16 2013; 7 2012; 126 2002; 49 1992; 7 2012; 175 2013; 17 2010; 24 2013; 16 2004; 34 1984; 13 2011; 21 2008; 24 2011; 23 2011; 27 2012; 23 2012; 22 2005; 78 2012 2011 2010 2013; 40 2000; 22 2008; 19 2002; 6 2007; 122 2013; 42 2009 2008 2008; 12 1992 2002 2011; 174 2011; 5 2010; 40 2009; 28 2010; 86 2005; 19 2006; 83 2011; 106 2012; 1 2013; 35 2005; 9 2005a; 9 2014 2013 2009; 4 2012; 6 2012; 7 2012; 88 2012; 42 2009; 39 Johnston (2023022801271406300_) 2008 Bernard (2023022801271406300_) 2010; 86 Wang (2023022801271406300_) 2005; 78 McCreesh (2023022801271406300_) 2012; 23 White (2023022801271406300_) 2012; 88 R Core Team (2023022801271406300_) 2012 Handcock (2023022801271406300_) 2011 Handcock (2023022801271406300_) 2012 Heckathorn (2023022801271406300_) 2002; 49 Burt (2023022801271406300_) 2012; 22 Handcock (2023022801271406300_) 2013 Lansky (2023022801271406300_) 2012; 6 Heimer (2023022801271406300_) 2005; 9 de Mello (2023022801271406300_) 2008 Magnani (2023022801271406300_) 2005; 19 Salganik (2023022801271406300_) 2012; 23 Montealegre (2023022801271406300_) 2013; 17 Johnston (2023022801271406300_) 2013; 17 Poon (2023022801271406300_) 2009; 4 Brewer (2023022801271406300_) 2000; 22 Volz (2023022801271406300_) 2008; 24 Salganik (2023022801271406300_) 2011; 174 Broadhead (2023022801271406300_) 2008; 19 Mills (2023022801271406300_) 2012; 126 Heckathorn (2023022801271406300_) 1997; 44 Lu (2023022801271406300_) 2013; 7 Handcock (2023022801271406300_) 2009 Gile (2023022801271406300_) 2010; 40 Lansky (2023022801271406300_) 2007; 122 Johnston (2023022801271406300_) 2013 Johnston (2023022801271406300_) 2013; 24 Malekinejad (2023022801271406300_) 2008; 12 Wejnert (2023022801271406300_) 2008; 37 Szwarcwald (2023022801271406300_) 2011; 57 Bengtsson (2023022801271406300_) 2010; 24 Goel (2023022801271406300_) 2009; 28 Goel (2023022801271406300_) 2010; 107 UNAIDS (2023022801271406300_) 2010 Lu (2023022801271406300_) 2012; 175 Marsden (2023022801271406300_) 1990; 16 Salganik (2023022801271406300_) 2004; 34 Barbosa Júnior (2023022801271406300_) 2011; 27 Gelman (2023022801271406300_) 1992; 7 Ouellet (2023022801271406300_) 2008; 19 Gile (2023022801271406300_) 2011; 106 Mouw (2023022801271406300_) 2012; 42 Scott (2023022801271406300_) 2008; 19 Ramirez-Valles (2023022801271406300_) 2005; 9 Rudolph (2023022801271406300_) 2013; 17 Wejnert (2023022801271406300_) 2009; 39 Johnston (2023022801271406300_) 2013; 40 Nesterko (2023022801271406300_) 2014 Stormer (2023022801271406300_) 2006; 83 Kerr (2023022801271406300_) 2011; 23 Johnston (2023022801271406300_) 2008; 12 Rudolph (2023022801271406300_) 2011; 21 Tomas (2023022801271406300_) 2011; 5 Gile (2023022801271406300_) 2011 Lu (2023022801271406300_) 2013; 35 Borgatti (2023022801271406300_) 2002 Frost (2023022801271406300_) 2006; 83 Raftery (2023022801271406300_) 1992 McCreesh (2023022801271406300_) 2013; 16 Yamanis (2023022801271406300_) 2013; 42 Bernard (2023022801271406300_) 1984; 13 Wejnert (2023022801271406300_) 2012; 16 Liu (2023022801271406300_) 2012; 1 Heckathorn (2023022801271406300_) 2002; 6 Iguchi (2023022801271406300_) 2009; 86 Bengtsson (2023022801271406300_) 2012; 7 |
| References_xml | – reference: Johnston, L. G., Khanam, R., Reza, M., Khan, S. I., Banu, S., Alam, M. S., Rahman, M. and Azim, T. (2008) The effectiveness of respondent driven sampling for recruiting males who have sex with males in Dhaka, Bangladesh. AIDS Behav., 12, 294-304. – reference: Scott, G. (2008) "They got their program, and I got mine": a cautionary tale concerning the ethical implications of using respondent-driven sampling to study injection drug users. Int. J. Drug Poly, 19, 42-51. – reference: Bengtsson, L. and Thorson, A. (2010) Global HIV surveillance among MSM: is risk behavior seriously underestimated? AIDS, 24, 2301-2303. – reference: Tomas, A. and Gile, K. J. (2011) The effect of differential recruitment, non-response and non-recruitment on estimators for respondent-driven sampling. Electron. J. Statist., 5, 899-934. – reference: Lu, X. (2013) Linked ego networks: improving estimate reliability and validity with respondent-driven sampling. Socl Netwrks, 35, 669-685. – reference: Stormer, A., Tun, W., Guli, L., Harxhi, A., Bodanovskaia, Z., Yakovleva, A., Rusakova, M., Levina, O., Bani, R., Rjepaj, K. and Bino, S. (2006) An analysis of respondent driven sampling with injection drug users (IDU) in Albania and the Russian Federation. J. Urb. Hlth, 83, 73-82. – reference: Wang, J., Carlson, R. G., Falck, R. S., Siegal, H. A., Rahman, A. and Li, L. (2005) Respondent-driven sampling to recruit MDMA users: a methodological assessment. Drug Alc. Depend., 78, 147-157. – reference: Heckathorn, D., Semaan, S., Broadhead, R. and Hughes, J. (2002) Extensions of respondent-driven sampling: a new approach to the study of injection drug users aged 18-25. AIDS Behav., 6, 55-67. – reference: Johnston, L. G., Prybylski, D., Raymond, H. F., Mirzazadeh, A., Manopaiboon, C. and McFarland, W. (2013) Incorporating the service multiplier method in respondent-driven sampling surveys to estimate the size of hidden and hard-to-reach populations. Sexlly Transmttd Dis., 40, 304-310. – reference: White, R. G., Lansky, A., Goel, S., Wilson, D., Hladik, W., Hakim, A. and Frost, S. D. (2012) Respondent driven sampling-where we are and where should we be going? Sexlly Transmttd Infectns, 88, 397-399. – reference: Wejnert, C. (2009) An empirical test of respondent-driven sampling: point estimates, variance, degree measures, and out-of-equilibrium data. Sociol. Methodol., 39, 73-116. – reference: Burt, R. D. and Thiede, H. (2012) Evaluating consistency in repeat surveys of injection drug users recruited by respondent-driven sampling in the Seattle area: results from the NHBS-IDU1 and NHBS-IDU2 surveys. Ann. Epidem., 22, 354-363. – reference: Heckathorn, D. D. (2002) Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hidden populations. Socl Prob., 49, 11-34. – reference: Iguchi, M. Y., Ober, A. J., Berry, S. H., Fain, T., Heckathorn, D. D., Gorbach, P. M., Heimer, R., Kozlov, A., Ouellet, L. J., Shoptaw, S. and Zule, W. A. (2009) 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. J. Urb. Hlth, 86, suppl. 1, 5-31. – reference: Johnston, L. G., Malekinejad, M., Kendall, C., Iuppa, I. M. and Rutherford, G. W. (2008) Implementation challenges to using respondent-driven sampling methodology for HIV biological and behavioral surveillance: field experiences in international settings. AIDS Behav., 12, suppl. 1, 131-141. – reference: Lansky, A., Drake, A., Wejnert, C., Pham, H., Cribbin, M. and Heckathorn, D. D. (2012) Assessing the assumptions of respondent-driven sampling in the National HIV Behavioral Surveillance System among injecting drug users. Open AIDS J., 6, 77-82. – reference: Frost, S. D., Brouwer, K. C., Firestone Cruz, M. A., Ramos, R., Ramos, M. E., Lozada, R. M., Magis-Rodriguez, C. and Strathdee, S. A. (2006) Respondent-driven sampling of injection drug users in two US-Mexico border cities: recruitment dynamics and impact on estimates of HIV and Syphilis prevalence. J. Urb. Hlth, 83, 83-97. – reference: Bernard, H. R., Killworth, P., Kronenfeld, D. and Sailer, L. (1984) The problem of informant accuracy: the validity of retrospective data. A. Rev. Anthrop., 13, 495-517. – reference: Lu, X., Malmros, J., Liljeros, F. and Britton, T. (2013) Respondent-driven sampling on directed networks. Electron. J. Statist., 7, 292-322. – reference: Yamanis, T. J., Merli, M. G., Neely, W. W., Tian, F. F., Moody, J., Tu, X. and Gao, E. (2013) An empirical analysis of the impact of recruitment patterns on RDS estimates among a socially ordered population of female sex workers in China. Sociol. Meth. Res., 42, 392-425. – reference: Volz, E. and Heckathorn, D. D. (2008) Probability based estimation theory for respondent driven sampling. J. Off. Statist., 24, 79-97. – reference: Gile, K. J. (2011) Improved inference for respondent-driven sampling data with application to HIV prevalence estimation. J. Am. Statist. Ass., 106, 135-146. – reference: McCreesh, N., Tarsh, M. N., Seeley, J., Katongole, J. and White, R. G. (2013) Community understanding of respondent-driven sampling in a medical research setting in Uganda: importance for the use of RDS for public health research. Int. J. Socl Res. Methodol., 16, 269-284. – reference: Rudolph, A. E., Fuller, C. M. and Latkin, C. (2013) The importance of measuring and accounting for potential biases in respondent-driven samples. AIDS Behav., 17, 2244-2252. – reference: Magnani, R., Sabin, K., Saidel, T. and Heckathorn, D. (2005) Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS, 19, suppl., S67-S72. – reference: Salganik, M. J. (2012) Commentary: Respondent-driven sampling in the real world. Epidemiology, 23, 148-150. – reference: Johnston, L. G., Caballero, T., Dolores, Y. and Values, H. M. (2013) HIV, Hepatitis B/C and Syphilis prevalence and risk behaviors among gay/trans/men who have sex with men, Dominican Republic. Int. J. STD AIDS, 24313-321. – reference: Lansky, A., Abdul-Quader, A. S., Cribbin, M., Hall, T., Finlayson, T. J., Garfein, R. S., Lin, L. S. and Sullivan, P. S. (2007) Developing an HIV behavioral surveillance system for injecting drug users: the National HIV Behavioral Surveillance System. Publ. Hlth Rep., 122, suppl. 1, 48-55. – reference: Goel, S. and Salganik, M. J. (2009) Respondent-driven sampling as Markov chain Monte Carlo. Statist. Med., 28, 2202-2229. – reference: Nesterko, S. and Blitzstein, J. (2014) Bias-variance and breadth-depth tradeoffs in respondent-driven sampling. J. Statist. Computn Simuln, to be published. – reference: Liu, H., Li, J., Ha, T. and Li, J. (2012) Assessment of random recruitment assumption in respondent-driven sampling in egocentric network data. Socl Netwrkng, 1, 13-21. – reference: Kerr, L. R. F. S., Kendall, C., Pontes, M. K., Werneck, G. L., McFarland, W., Mello, M. B., Martins, T. A. and Macena, R. H. M. (2011) Selective participation in a RDS survey among MSM in Ceara, Brazil: a qualitative and quantitative assessment. J. Bras. Doenc. Sexmnte Transmiss., 23, 126-133. – reference: Ramirez-Valles, J., Heckathorn, D. D., Vázquez, R., Diaz, R. M. and Campbell, R. T. (2005b) The fit between theory and data in respondent-driven sampling: Response to Heimer. AIDS Behav., 9, 409-414. – reference: Heimer, R. (2005) Critical issues and further questions about respondent-driven sampling: comment on Ramirez-Valles, et al. (2005). AIDS Behav., 9, 403-408. – reference: Bernard, H. R., Hallett, T., Iovita, A., Johnsen, E. C., Lyerla, R., McCarty, C., Mahy, M., Salganik, M. J., Saliuk, T., Scutelniciuc, O., Shelley, G. A., Sirinirund, P., Weir, S. and Stroup, D. F. (2010) Counting hard-to-count populations: the network scale-up method for public health. Sexlly Transmttd Infect., 86, suppl. 2, ii11-ii15. – reference: Marsden, P. V. (1990) Network data and measurement. A. Rev. Sociol., 16, 435-463. – reference: Ramirez-Valles, J., Heckathorn, D. D., Vázquez, R., Diaz, R. M. and Campbell, R. T. (2005a) From networks to populations: the development and application of respondent-driven sampling among IDUs and Latino gay men. AIDS Behav., 9, 387-402. – reference: Gile, K. J. and Handcock, M. S. (2010) Respondent-driven sampling: an assessment of current methodology. Sociol. Methodol., 40, 285-327. – reference: Mills, H., Colijn, C., Vickerman, P., Leslie, D., Hope, V. and Hickman, M. (2012) Respondent driven sampling and community structure in a population of injecting drug users, Bristol, UK. Drug Alc. Depend., 126, 324-332. – reference: Barbosa Júnior, A., Pati Pascom, A. R., Szwarcwald, C. L., Kendall, C. and McFarland, W. (2011) Transfer of sampling methods for studies on most-at-risk populations (MARPs) in Brazil. Cad. Sde Publ., 27, suppl. S1, S36-S44. – reference: Ouellet, L. J. (2008) Cautionary comments on an ethnographic tale gone wrong. Int. J. Drug Poly, 19, 238-240. – reference: Rudolph, A. E., Crawford, N. D., Latkin, C., Heimer, R., Benjamin, E. O., Jones, K. C. and Fuller, C. M. (2011) Subpopulations of illicit drug users reached by targeted street outreach and respondent-driven sampling strategies: implications for research and public health practice. Ann. Epidem., 21, 280-289. – reference: Heckathorn, D. D. (1997) Respondent-driven sampling: a new approach to the study of hidden populations. Socl Prob., 44, 174-199. – reference: Gelman, A. and Rubin, D. B. (1992) Inference from iterative simulation using multiple sequences. Statist. Sci., 7, 457-472. – reference: Lu, X., Bengtsson, L., Britton, T., Camitz, M., Kim, B. J., Thorson, A. and Liljeros, F. (2012) The sensitivity of respondent-driven sampling. J. R. Statist. Soc. A, 175, 191-216. – reference: Brewer, D. D. 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| Snippet | Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for human... Summary Respondent‐driven sampling (RDS) is a widely used method for sampling from hard‐to‐reach human populations, especially populations at higher risk for... Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for HIV. Data... |
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| SubjectTerms | Acquired immune deficiency syndrome AIDS Coupons Data collection Diagnostic software Diagnostics Diseases Estimation bias Estimators Exploratory data analysis Hard-to-reach populations Health risk assessment HIV Human immunodeficiency virus Inference Link tracing sampling Non-ignorable design Organizations Population Population estimates Populations Public health Respiratory distress syndrome Respondent-driven sampling Risk Sampling Sampling bias Sampling techniques Social networks Statistical analysis Statistics Survey sampling |
| Title | Diagnostics for respondent-driven sampling |
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