Murray CJL, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012; 380(9859): 2197–2223. doi:10.1016/S0140-6736(12)61689-4.
Article
PubMed
Google Scholar
Padian NS, McCoy SI, Karim SSA, et al. HIV prevention transformed: the new prevention research agenda. Lancet. 2011; 378(9787): 269–278. doi:10.1016/S0140-6736(11)60877-5.
PubMed Central
Article
PubMed
Google Scholar
Schwartländer B, Stover J, Hallett T, et al. Towards an improved investment approach for an effective response to HIV/AIDS. Lancet. 2011; 377(9782): 2031–2041. doi:10.1016/S0140-6736(11)60702-2.
Article
PubMed
Google Scholar
Heckman TG, Kelly J a, Bogart LM, Kalichman SC, Rompa DJ. HIV risk differences between African-American and white men who have sex with men. J Natl Med Assoc. 1999;91(2):92–100. Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2608406&tool=pmcentrez&rendertype=abstract. Accessed September 2014.
Torian LV, Makki HA, Menzies IB, Murrill CS. Department of Health sexually transmitted disease clinics, a decade of serosurveillance finds that racial disparities and associations between HIV and gonorrhea persist. Sex Transm Dis. 2002; 29(2): 73–78.
Article
PubMed
Google Scholar
San Francisco Department of Public Health. HIV/AIDS Epidemiology Annual Report. San Francisco HIV Epidemiology Section. 2010.
Sudhinaraset M, Raymond HF, McFarland W. Convergence of HIV prevalence and inter-racial sexual mixing among men who have sex with men, San Francisco, 2004-2011. AIDS Behav. 2013; 17(4): 1550–1556. doi:10.1007/s10461-012-0370-3.
Article
PubMed
Google Scholar
Scott HM, Bernstein KT, Raymond HF, Kohn R, Klausner JD. Racial/ethnic and sexual behavior disparities in rates of sexually transmitted infections, San Francisco, 1999-2008. BMC Public Health. 2010; 10: 315. doi:10.1186/1471-2458-10-315.
PubMed Central
Article
PubMed
Google Scholar
International Working Group for Disease Monitoring and Forcasting. Capture-recapture and multiple-record systems estimation II: applications in human diseases. Am J Epidemiol. 1995; 142(10): 1059–1068.
Google Scholar
International Working Group for Disease Monitoring and Forcasting. Capture-recapture and multiple-record systems estimation. I: History and theoretical development. Am J …. 1995;142(10):1047–1058. Available at: http://hub.hku.hk/handle/10722/82976. Accessed April 28, 2013.
Jones HE, Hickman M, Welton NJ, De Angelis D, Harris RJ, Ades AE. Recapture or precapture? Fallibility of standard capture-recapture methods in the presence of referrals between sources. Am J Epidemiol. 2014; 179(11): 1383–1393. doi:10.1093/aje/kwu056.
PubMed Central
Article
PubMed
Google Scholar
Johnston LG, Prybylski D, Raymond HF, Mirzazadeh A, Manopaiboon C, McFarland W. Incorporating the service multiplier method in respondent-driven sampling surveys to estimate the size of hidden and hard-to-reach populations: case studies from around the world. Sex Transm Dis. 2013; 40: 304–310. doi:10.1097/OLQ.0b013e31827fd650.
Article
PubMed
Google Scholar
Salganik MJ, Fazito D, Bertoni N, Abdo AH, Mello MB, Bastos FI. 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 Epidemiol. 2011; 174(10): 1190–1196. doi:10.1093/aje/kwr246.
PubMed Central
Article
PubMed
Google Scholar
Fuqua V, Chen Y-H, Packer T, et al. Using social networks to reach Black MSM for HIV testing and linkage to care. AIDS Behav. 2012; 16(2): 256–265. doi:10.1007/s10461-011-9918-x.
Article
PubMed
Google Scholar
Handcock M, Gile K, Mar C. Estimating hidden population size using respondent-driven sampling data. arXiv Prepr arXiv12096241. 2012. Available at: http://arxiv.org/pdf/1209.6241v1.pdf. Accessed February 3, 2014.
Heckathorn D. Respondent-driven sampling: a new approach to the study of hidden populations. Soc Probl. 1997;44:174–199. Available at: http://www.jstor.org/stable/10.2307/3096941. Accessed April 28, 2013.
Heckathorn D. Respondent-driven sampling II: deriving valid population estimates from chain-referral samples of hidden populations. Soc Probl. 2002;49(1):11–34. Available at: http://www.jstor.org/stable/10.1525/sp.2002.49.1.11. Accessed April 28, 2013.
Gile KJ, Handcock MS. Respondent-driven sampling: an assessment of current methodology. Sociol Methodol. 2010; 40(1): 285–327. doi:10.1111/j.1467-9531.2010.01223.x.
PubMed Central
Article
PubMed
Google Scholar
Nair VN, Wang PC. Maximum likelihood estimation under a successive model discovery sampling. Technometrics. 1989; 31(4): 423–436.
Article
Google Scholar
West M. Inference in successive sampling discovery models. J Econ. 1996; 75(1): 217–238. doi:10.1016/0304-4076(95)01777-1.
Article
Google Scholar
Hamra G, MacLehose R, Richardson D. Markov chain Monte Carlo: an introduction for epidemiologists. Int J Epidemiol. 2013; 42(2): 627–634. doi:10.1093/ije/dyt043.
PubMed Central
Article
PubMed
Google Scholar
StataCorp. Stata Statistical Software: release 12. College Station, TX: StataCorp LP. 2011.
R Core Team. R: a language and environment for statistical computing. 2014. Available at: http://www.r-project.org. Accessed July 2014.
Handcock MS, Fellows IE, Gile KJ. RDS Analyst: software for the analysis of respondent-driven sampling data, Version 0.42. 2014. http://hpmrg.org. Accessed July 2014.
Gile KJ. Improved inference for respondent-driven sampling data with application to HIV prevalence estimation. J Am Stat Assoc. 2011; 106(493): 135–146. doi:10.1198/jasa.2011.ap09475.
Article
CAS
Google Scholar
Bureau USC. Sex by age universe : total population 2006-2010 American community survey selected population tables. 2014:1–2. Available at: http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_10_SF4_B01001&prodType=table. Accessed November 2014.
Raymond HF, Bereknyei S, Berglas N, Hunter J, Ojeda N, McFarland W. Estimating population size, HIV prevalence and HIV incidence among men who have sex with men: a case example of synthesising multiple empirical data sources and methods in San Francisco. Sex Transm Infect. 2013; 89(5): 383–387. doi:10.1136/sextrans-2012-050675.
Article
PubMed
Google Scholar
Rudolph AE, Fuller CM, Latkin C. The importance of measuring and accounting for potential biases in respondent-driven samples. AIDS Behav. 2013; 17(6): 2244–2252. doi:10.1007/s10461-013-0451-y.
PubMed Central
Article
PubMed
Google Scholar
Kendall C, Kerr LRFS, Gondim RC, et al. An empirical comparison of respondent-driven sampling, time location sampling, and snowball sampling for behavioral surveillance in men who have sex with men, Fortaleza Brazil. AIDS Behav. 2008; 12(SUPPL. 1): 97–104. doi:10.1007/s10461-008-9390-4.
Article
Google Scholar
Handcock M, Gile K. SSPSE: estimating hidden population size using respondent driven sampling data. 2015. Available at: http://hpmrg.org. Accessed July 2014.
Malekinejad M, Johnston LG, Kendall C, Kerr LRFS, Rifkin MR, Rutherford GW. Using respondent-driven sampling methodology for HIV biological and behavioral surveillance in international settings: a systematic review. AIDS Behav. 2008; 12(4 Suppl): S105–S130. doi:10.1007/s10461-008-9421-1.
Article
PubMed
Google Scholar
UNAIDS/WHO Working Group on Global HIV/AIDS and STI Surveillance. Guidelines on Estimating the Size of Populations Most at Risk to HIV. Geneva, Switzerland; 2011.