期刊
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY
卷 178, 期 3, 页码 619-639出版社
WILEY
DOI: 10.1111/rssa.12091
关键词
Exponential family random graph model; Hard-to-reach population sampling; Link tracing; Network sampling; Social networks
资金
- Eunice Kennedy Shriver National Institute of Child Health and Development [1R21HD063000, 5R21HD075714-02]
- National Science Foundation [MMS-0851555, MMS-1357619, SES-1230081]
- National Agricultural Statistics Service
- Office of Naval Research [N00014-08-1-1015]
- Eunice Kennedy Shriver National Institute of Child Health and Human Development [R24 HD042828]
- National Institute of Child Health and Development [R24-HD041022]
- Direct For Social, Behav & Economic Scie
- Divn Of Social and Economic Sciences [1357619] Funding Source: National Science Foundation
- Divn Of Social and Economic Sciences
- Direct For Social, Behav & Economic Scie [1230081] Funding Source: National Science Foundation
Respondent-driven sampling is a widely used method for sampling hard-to-reach human populations by link tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to compute the sampling weights for traditional design-based inference directly, and likelihood inference requires modelling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared with existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of the prevalence of human immunodeficiency virus in a high-risk population.
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