B-Graph Sampling to Estimate the Size of a Hidden Population

Spreen Marinus () and Bogaerts Stefan ()
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Spreen Marinus: Stenden University of Applied Sciences-School of Social Work and Art Therapies, Rengerslaan 8 Leeuwarden 8917 DD, The Netherlands.
Bogaerts Stefan: Tillburg University, Department of Developmental Psychology, Warandelaan 2, 5037 AB Tilburg, The Netherlands.

Journal of Official Statistics, 2015, vol. 31, issue 4, 723-736

Abstract: Link-tracing designs are often used to estimate the size of hidden populations by utilizing the relational links between their members. A major problem in studies of hidden populations is the lack of a convenient sampling frame. The most frequently applied design in studies of hidden populations is respondent-driven sampling in which no sampling frame is used. However, in some studies multiple but incomplete sampling frames are available. In this article, we introduce the B-graph design that can be used in such situations. In this design, all available incomplete sampling frames are joined and turned into one sampling frame, from which a random sample is drawn and selected respondents are asked to mention their contacts. By considering the population as a bipartite graph of a two-mode network (those from the sampling frame and those who are not on the frame), the number of respondents who are directly linked to the sampling frame members can be estimated using Chao’s and Zelterman’s estimators for sparse data. The B-graph sampling design is illustrated using the data of a social network study from Utrecht, the Netherlands.

Keywords: Network sampling; capture recapture; hidden populations (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:31:y:2015:i:4:p:723-736:n:10

DOI: 10.1515/jos-2015-0042

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