Improved Inference for Respondent-Driven Sampling Data With Application to HIV Prevalence Estimation
Improved Inference for Respondent-Driven Sampling Data With Application to HIV Prevalence Estimation
复制标题
DOI：
10.1198/jasa.2011.ap09475
复制
发表时间：
2011-03-01
影响因子：
3.7
通讯作者：
Gile, Krista J.
中科院分区：
文献类型：
--
作者：
Gile, Krista J.
受访者驱动抽样是链接追踪网络抽样的一种形式，被广泛用于研究难以到达的人群，通常用于估计人口比例。前人对这一过程的处理使用了替换近似，我们发现这会导致大样本分数估计的偏差和兴趣特征的差分网络连通性。我们将受访者驱动抽样视为一个连续抽样过程。与现有的表示法不同，我们的方法尊重过程的基本无替换特征，同时收敛到现有的小样本部分的替换表示法和全总体样本的样本均值.我们提出了一种基于受访者驱动的抽样数据的总体均值的连续抽样估计器，并在已知隐藏总体的大小的情况下证明了该估计器的优越性能.我们给出了对未知种群规模的敏感性分析。此外，我们注意到，与其他现有的估计量一样，我们的新估计量也会因为初始样本的选择而产生偏差。使用在两个国家的三个人口中收集的数据，我们说明了这种方法在具有不同特征的人口中的应用。我们的结论是，连续抽样估计量改进了现有的估计量，并且在总体规模未知的情况下也可以作为一种诊断工具。这篇文章在网上有补充材料。
Respondent-driven sampling is a form of link-tracing network sampling, which is widely used to study hard-to-reach populations, often to estimate population proportions. Previous treatments of this process have used a with-replacement approximation, which we show induces bias in estimates for large sample fractions and differential network connectedness by characteristic of interest.We present a treatment of respondent-driven sampling as a successive sampling process. Unlike existing representations, our approach respects the essential without-replacement feature of the process, while converging to an existing with-replacement representation for small sample fractions, and to the sample mean for a full-population sample.We present a successive-sampling based estimator for population means based on respondent-driven sampling data, and demonstrate its super,or performance when the size of the hidden population is known. We present sensitivity analyses for unknown population sizes. In addition, we note that like other existing estimators, our new estimator is subject to bias induced by the selection of the initial sample. Using data collected among three populations in two countries, we illustrate the application of this approach to populations with varying characteristics. We conclude that the successive sampling estimator improves on existing estimators, and can also be used as a diagnostic tool when population size is not known. This article has supplementary material online.