5. Sampling and Estimation in Hidden Populations Using Respondent-Driven Sampling

2004/11/26 by Matthew Salganik, Matthew J. Salganik, Douglas D. Heckathorn · 9 citations
Engineering · Mathematics · Medicine · Physics and Astronomy · #Census and Population Estimation #Complex Network Analysis Techniques #Computer science #Computer vision #Demography #Econometrics #Engineering #Estimation #HIV, Drug Use, Sexual Risk #Law #Mathematics #Population #Respondent #Sample (material) #Sampling (signal processing) #Sampling design #Snowball sampling #Sociology #Statistics #Trait

paper · doi:10.1111/j.0081-1750.2004.00152.x

openalex publication_date 2004/11/26 · crossref created 2004/11/26 · crossref issued 2004/12/01 · crossref published 2004/12/01 · crossref published-online 2004/12/01 · crossref published-print 2004/12/01 · crossref deposited 2025/03/10 · openalex created_date 2025/10/10 · crossref indexed 2026/07/31 · openalex updated_date 2026/07/31

Abstract

Standard statistical methods often provide no way to make accurate estimates about the characteristics of hidden populations such as injection drug users, the homeless, and artists. In this paper, we further develop a sampling and estimation technique called respondent-driven sampling, which allows researchers to make asymptotically unbiased estimates about these hidden populations. The sample is selected with a snowball-type design that can be done more cheaply, quickly, and easily than other methods currently in use. Further, we can show that under certain specified (and quite general) conditions, our estimates for the percentage of the population with a specific trait are asymptotically unbiased. We further show that these estimates are asymptotically unbiased no matter how the seeds are selected. We conclude with a comparison of respondent-driven samples of jazz musicians in New York and San Francisco, with corresponding institutional samples of jazz musicians from these cities. The results show that some standard methods for studying hidden populations can produce misleading results.

Citations

• Networks, Dynamics, and the Small‐World Phenomenon
• Relational Analysis: The Study of Social Organizations with Survey Methods
• Estimation On the Basis of Snowball Samples: How To Weight?
• Assortative Mixing in Networks
• Birds of a Feather: Homophily in Social Networks
• Respondent-Driven Sampling II: Deriving Valid Population Estimates from Chain-Referral Samples of Hidden Populations
• The Structure and Function of Complex Networks
• Snowball Sampling: Problems and Techniques of Chain Referral Sampling
• Respondent-Driven Sampling: A New Approach to the Study of Hidden Populations
• Random graphs with arbitrary degree distributions and their applications
• Snowball Sampling

Cited by

• 7. Respondent-Driven Sampling: An Assessment of Current Methodology
• 3. An Empirical Test of Respondent-Driven Sampling: Point Estimates, Variance, Degree Measures, and Out-of-Equilibrium Data
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• Immunization strategies in networks with missing data
• Measuring transnational social fields through binational link-tracing sampling
• The One-Child Policy in Shanghai: Acceptance and Internalization
• Is Child to Adult as Victim is to Criminal?
• Random Walks on Simplicial Complexes and the Normalized Hodge 1-Laplacian
• Acculturative Stress, Psychological Distress, and Religious Coping Among Latina Young Adult Immigrants
• Random networks with tunable degree distribution and clustering
• Measuring Network Sizes in the Context of Respondent Driven Sampling: Evidence from Two Independent Surveys