使用多重应答驱动抽样调查进行人口规模估计
Population Size Estimation Using Multiple Respondent-Driven Sampling Surveys.
作者信息
Kim Brian J, Handcock Mark S
机构信息
Lecturer in the Joint Program in Survey Methodology, University of Maryland, 1218 LeFrak Hall, 7251 Preinkert Dr., College Park, MD 20742, USA.
Professor at the University of California, 8125 Math Sciences Bldg., Box 951554, Los Angeles, CA 90095, USA.
出版信息
J Surv Stat Methodol. 2019 Dec 7;9(1):94-120. doi: 10.1093/jssam/smz055. eCollection 2021 Feb.
Respondent-driven sampling (RDS) is commonly used to study hard-to-reach populations since traditional methods are unable to efficiently survey members due to the typically highly stigmatized nature of the population. The number of people in these populations is of primary global health and demographic interest and is usually hard to estimate. However, due to the nature of RDS, current methods of population size estimation are insufficient. We introduce a new method of estimating population size that uses concepts from capture-recapture methods while modeling RDS as a successive sampling process. We assess its statistical validity using information from the CDC's National HIV Behavioral Surveillance system in 2009 and 2012.
应答驱动抽样（RDS）通常用于研究难以接触到的人群，因为传统方法由于这类人群通常具有高度污名化的性质，无法有效地对其成员进行调查。这些人群的数量是全球主要的健康和人口统计学关注点，通常很难估计。然而，由于RDS的性质，目前的人口规模估计方法并不充分。我们引入了一种新的人口规模估计方法，该方法采用捕获再捕获方法的概念，同时将RDS建模为一个连续抽样过程。我们利用美国疾病控制与预防中心（CDC）2009年和2012年国家艾滋病行为监测系统的信息评估了其统计有效性。
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