The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Respondent‐driven sampling as Markov chain Monte Carlo
Open accessAbstract
Respondent‐driven sampling (RDS) is a recently introduced, and now widely used, technique for estimating disease prevalence in hidden populations. RDS data are collected through a snowball mechanism, in which current sample members recruit future sample members. In this paper we present RDS as Markov chain Monte Carlo importance sampling, and we examine the effects of community structure and the recruitment procedure on the variance of RDS estimates. Past work has assumed that the variance of RDS estimates is primarily affected by segregation between healthy and infected individuals. We examine an illustrative model to show that this is not necessarily the case, and that bottlenecks anywhere in the networks can substantially affect estimates. We also show that variance is inflated by a common design feature in which the sample members are encouraged to recruit multiple future sample members. The paper concludes with suggestions for implementing and evaluating RDS studies. Copyright © 2009 John Wiley & Sons, Ltd.
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Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
General methods for monitoring convergence of iterative simulations
Brooks, S. P., & Gelman, A. (1998) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.1998.10474787 · Cited by 6,045
Practical markov chain monte carlo
Geyer, C. J. (1992) · Statistical Science · doi:10.1214/ss/1177011137 · Cited by 2,045
Malekinejad, M., Johnston, L. G., Kendall, C., Kerr, L. R. F. S., Rifkin, M. R., & Rutherford, G. W. (2008) · AIDS and Behavior · doi:10.1007/s10461-008-9421-1 · Cited by 433
Cited by
Comment: Snowball versus Respondent-Driven Sampling
Heckathorn, D. D. (2011) · Sociological Methodology · doi:10.1111/j.1467-9531.2011.01244.x · Cited by 930
A Survey of Statistical Network Models
Goldenberg, A., Zheng, A. X., Fienberg, S. E., & Airoldi, E. M. (2010) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000005 · Cited by 819
Network Sampling: From Snowball and Multiplicity to Respondent-Driven Sampling
Heckathorn, D. D., & Cameron, C. J. (2017) · Annual Review of Sociology · doi:10.1146/annurev-soc-060116-053556 · Cited by 307
Metadata
- Authors
- Goel, S., & Salganik, M. J.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2009-07
- Volume
- 28
- Issue
- 17
- Pages
- 2202-2229
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2140610008
- Cited by
- 203
- References
- 5
- FWCI
- 16.12
- Type
- journal article
- Language
- en
- Open access
- green
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