This paper deals with the estimation of population sizes for respondent-driven sampling (RDS), a variant of link-tracing sampling that leverages social networks over a number of waves to recruit individuals from hidden populations. The RDS process is mostly controlled by individual participants who might report on recruitment proposals, or nominations, that they have received or given. By considering all nominations given or received over a time period, one can create a capture-recapture dataset in which units are individuals who have received at least one nomination and capture occasions are either time intervals or recruitment waves, with the goal of estimating the size $N$ of the hidden population. In this paper, we argue that the underlying process that generated the RDS nomination data is that of a capture-recapture experiment. We then proposed a methodology for the estimation of the population size and investigated its performance against departures from classical capture-recapture assumptions.
翻译:本文件涉及对受调查者推动的抽样(RDS)的人口规模的估计,这是在一系列波浪中利用社会网络从隐蔽人口中招募个人的链接追踪抽样的变种,其中,RDS过程主要由个别参与者控制,他们可以报告他们收到或提供的征聘建议或提名;通过考虑在一段时间内提出或收到的所有提名,人们可以建立一个抓获数据集,其中获得至少一个提名和捕捉机会的单位为个人,可以是时间间隔,也可以是招聘浪潮,目的是估计隐蔽人口的规模。 在本文件中,我们提出产生RDS提名数据的基本过程是捕捉和捕捉试验,然后我们提出了估计人口规模的方法,并针对偏离传统捕捉假设的情况调查其表现。