Diagnostics for Respondent-driven Sampling.
Diagnostics for Respondent-driven Sampling.
复制标题
DOI：
10.1111/rssa.12059
复制
发表时间：
2015-01
期刊：
影响因子：
--
通讯作者：
Salganik MJ
中科院分区：
文献类型：
--
作者：
Gile KJ;Johnston LG;Salganik MJ
应答者驱动采样（RDS）是一种广泛使用的方法，用于从难以接触的人群中采样，特别是艾滋病毒高风险人群。通过社交网络上的同行推荐收集数据。RDS已被证明可用于许多困难环境中的数据收集，并被广泛使用。从RDS数据推断需要许多强有力的假设，因为抽样设计部分超出了研究人员的控制，部分未观察到。我们为大多数这些假设引入诊断工具，并将其应用于12个高危人群。这些诊断使研究人员能够更好地理解他们的数据，并鼓励未来对RDS的统计研究。
Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially populations at higher risk for HIV. Data are collected through peer-referral over social networks. RDS has proven practical for data collection in many difficult settings and is widely used. Inference from RDS data requires many strong assumptions because the sampling design is partially beyond the control of the researcher and partially unobserved. We introduce diagnostic tools for most of these assumptions and apply them in 12 high risk populations. These diagnostics empower researchers to better understand their data and encourage future statistical research on RDS.