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Respondent-Driven Sampling (RDS) is an approach to sampling design and inference in hard-to-reach human populations. Typically, a sampling frame is not available, and population members are difficult to identify or recruit from broader…

统计方法学 · 统计学 2012-09-28 Mark S. Handcock , Krista J. Gile , Corinne M. Mar

This work is concerned with the estimation of hard-to-reach population sizes using a single respondent-driven sampling (RDS) survey, a variant of chain-referral sampling that leverages social relationships to reach members of a hidden…

Estimating the size of stigmatized, hidden, or hard-to-reach populations is a major problem in epidemiology, demography, and public health research. Capture-recapture and multiplier methods have become standard tools for inference of hidden…

统计方法学 · 统计学 2015-05-01 Forrest W. Crawford , Jiacheng Wu , Robert Heimer

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…

统计方法学 · 统计学 2023-07-24 Mamadou Yauck

Researchers in many scientific fields make inferences from individuals to larger groups. For many groups however, there is no list of members from which to take a random sample. Respondent-driven sampling (RDS) is a relatively new sampling…

应用统计 · 统计学 2012-01-10 Xin Lu , Linus Bengtsson , Tom Britton , Martin Camitz , Beom Jun Kim , Anna Thorson , Fredrik Liljeros

Objective: Lack of representative data about hidden groups, like men who have sex with men (MSM), hinders an evidence-based response to the HIV epidemics. Respondent-driven sampling (RDS) was developed to overcome sampling challenges in…

In this article, we propose using network-based sampling strategies to estimate the number of unsheltered people experiencing homelessness within a given administrative service unit, known as a Continuum of Care. We demonstrate the…

A new estimation method is presented for network sampling designs, including Respondent Driven Sampling (RDS) and Snowball (SB) sampling. These types of link-tracing designs are essential for studies of hidden populations, such as people at…

统计方法学 · 统计学 2019-04-24 Steve Thompson

Respondent-driven sampling (RDS) is a widely used method for sampling from hard-to-reach human populations, especially groups most at-risk for HIV/AIDS. Data are collected through a peer-referral process in which current sample members…

统计方法学 · 统计学 2012-09-28 Krista J. Gile , Lisa G. Johnston , Matthew J. Salganik

Molecular HIV Surveillance (MHS) has been described as key to enabling rapid responses to HIV outbreaks. It operates by linking individuals with genetically similar viral sequences, which forms a network. A major limitation of MHS is that…

应用统计 · 统计学 2024-07-24 Ravi Goyal , Kevin Nguyen , Victor De Gruttola , Susan J Little , Colby Cohen , Natasha K Martin

Respondent-driven sampling (RDS) is currently widely used for the study of HIV/AIDS-related high risk populations. However, recent studies have shown that traditional RDS methods are likely to generate large variances and may be severely…

统计方法学 · 统计学 2012-10-17 Xin Lu

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…

统计方法学 · 统计学 2010-06-25 Krista J. Gile

Estimates of population size for hidden and hard-to-reach individuals are of particular interest to health officials when health problems are concentrated in such populations. Efforts to derive these estimates are often frustrated by a…

社会与信息网络 · 计算机科学 2017-02-01 Bilal Khan , Hsuan-Wei Lee , Kirk Dombrowski

Respondent-driven sampling (RDS) is a popular method for sampling hard-to-survey populations that leverages social network connections through peer recruitment. While RDS is most frequently applied to estimate the prevalence of infections…

统计方法学 · 统计学 2016-10-24 Ashton M. Verdery , Jacob C. Fisher , Nalyn Siripong , Kahina Abdesselam , Shawn Bauldry

Large Language Models (LLMs) excel in text generation and understanding, especially in simulating socio-political and economic patterns, serving as an alternative to traditional surveys. However, their global applicability remains…

计算机与社会 · 计算机科学 2025-01-28 Andrés Abeliuk , Vanessa Gaete , Naim Bro

Population size estimates for hidden and hard-to-reach populations are particularly important when members are known to suffer from disproportion health issues or to pose health risks to the larger ambient population in which they are…

社会与信息网络 · 计算机科学 2018-07-04 Bilal Khan , Hsuan-Wei Lee , Ian Fellows , Kirk Dombrowski

Key populations at high risk of HIV infection are critical for understanding and monitoring HIV epidemics, but global estimation is hampered by sparse, uneven data. We analyze data from 199 countries for female sex workers (FSW), men who…

应用统计 · 统计学 2025-09-16 Jiahao Zhang , Keith Sabin , Le Bao

Respondent-Driven Sampling (RDS) is a variant of link-tracing sampling techniques that aim to recruit hard-to-reach populations by leveraging individuals' social relationships. As such, an RDS sample has a graphical component which…

Respondent-driven sampling (RDS) is a commonly used method for acquiring data on hidden communities, i.e., those that lack unbiased sampling frames or face social stigmas that make their mem- bers unwilling to identify themselves. Obtaining…

社会与信息网络 · 计算机科学 2013-08-30 Christopher M. Homan , Vincent Silenzio , Randall Sell

The network scale-up method (NSUM) is a survey-based method for estimating the number of individuals in a hidden or hard-to-reach subgroup of a general population. In NSUM surveys, sampled individuals report how many others they know in the…

统计方法学 · 统计学 2021-11-19 Nathaniel Josephs , Dennis M. Feehan , Forrest W. Crawford
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