Estimating Population Size With Link-Tracing Sampling

• 成果类型: Article
• 署名作者: Vincent, Kyle; Thompson, Steve
• 署名单位: Bank of Canada; Simon Fraser University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2016.1212712
• 发表日期: 2017
• 页码: 1286-1295
• 关键词: capture-recapture data; social networks; colorado-springs; abundance

摘要

We present a new design and method for estimating the size of a hidden population best reached through a link-tracing design. The design is based on selecting initial samples at random and then adaptively tracing links to add new members. The inferential procedure involves the Rao-Blackwell theorem applied to a sufficient statistic markedly different from the usual one that arises in sampling from a finite population. The strategy involves a combination of link-tracing and mark-recapture estimation methods. An empirical application is described. The result demonstrates that the strategy can efficiently incorporate adaptively selected members of the sample into the inferential procedure. Supplementary materials for this article are available online.