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Related papers: Estimating Hidden Population Size using Respondent…

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Respondent-driven sampling (RDS) is widely used to study hidden or hard-to-reach populations by incentivizing study participants to recruit their social connections. The success and efficiency of RDS can depend critically on the nature of…

Methodology · Statistics 2025-01-06 Justin Weltz , Angela Yoon , Yichi Zhang , Alexander Volfovsky , Eric Laber

Sampling hidden populations is particularly challenging using standard sampling methods mainly because of the lack of a sampling frame. Respondent-driven sampling (RDS) is an alternative methodology that exploits the social contacts between…

Respondent driven sampling (RDS) is a method often used to estimate population properties (e.g. sexual risk behavior) in hard-to-reach populations. It combines an effective modified snowball sampling methodology with an estimation procedure…

Methodology · Statistics 2013-08-19 Jens Malmros , Naoki Masuda , Tom Britton

Respondent-driven sampling (RDS) is a sampling scheme used in socially connected human populations lacking a sampling frame. One of the first steps to make design-based inferences from RDS data is to estimate the sampling probabilities. A…

Methodology · Statistics 2025-03-19 Alejandro Sepulveda-Peñaloza , Isabelle S. Beaudry

Respondent-driven sampling (RDS) is a link-tracing sampling method that is especially suitable for sampling hidden populations. RDS combines an efficient snowball-type sampling scheme with inferential procedures that yield unbiased…

Methodology · Statistics 2016-03-15 Jens Malmros , Luis E. C. Rocha

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…

Social and Information Networks · Computer Science 2018-07-04 Bilal Khan , Hsuan-Wei Lee , Ian Fellows , Kirk Dombrowski

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…

Respondent-Driven Sampling is a method to sample hard-to-reach human populations by link-tracing over their social networks. Beginning with a convenience sample, each person sampled is given a small number of uniquely identified coupons to…

Methodology · Statistics 2011-08-02 Krista J. Gile , Mark S. Handcock

Respondent-Driven Sampling (RDS) is a form of link-tracing sampling, a sampling technique used for `hard-to-reach' populations that aims to leverage individuals' social relationships to reach potential participants. While the methodological…

Current methods for population mean estimation from data collected by Respondent Driven Sampling (RDS) are based on the Horvitz-Thompson estimator together with a set of assumptions on the sampling model under which the inclusion…

Methodology · Statistics 2014-11-10 Adityanand Guntuboyina , Russell Barbour , Robert Heimer

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…

Methodology · Statistics 2019-04-24 Steve Thompson

Respondent-driven sampling (RDS) is frequently used when sampling hard-to-reach and/or stigmatized communities. RDS utilizes a peer-driven recruitment mechanism where sampled individuals pass on participation coupons to at most $c$ of their…

Physics and Society · Physics 2014-11-19 Jens Malmros , Fredrik Liljeros , Tom Britton

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…

Methodology · Statistics 2012-10-17 Xin Lu

Respondent-driven sampling (RDS) is a method of chain referral sampling popular for sampling hidden and/or marginalized populations. As such, even under the ideal sampling assumptions, the performance of RDS is restricted by the underlying…

Methodology · Statistics 2017-11-02 Mohammad Khabbazian , Bret Hanlon , Zoe Russek , Karl Rohe

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…

Social and Information Networks · Computer Science 2017-02-01 Bilal Khan , Hsuan-Wei Lee , Kirk Dombrowski

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…

Social and Information Networks · Computer Science 2023-10-31 Zack W. Almquist , Ashley Hazel , Owen Kajfasz , Janelle Rothfolk , Claire Guilmette , Mary-Catherine Anderson , Larisa Ozeryansky , Amy Hagopian

Dual-record system (DRS) (equivalently two sample Capture-recapture experiment) model with time and behavioral response variation, has attracted much attention specifically in the domain of Official Statistics and Epidemiology. The relevant…

Methodology · Statistics 2019-08-09 Kiranmoy Chatterjee , Diganta Mukherjee

People who inject drugs are an important population to study in order to reduce transmission of blood-borne illnesses including HIV and Hepatitis. In this paper we estimate the HIV and Hepatitis C prevalence among people who inject drugs,…

Applications · Statistics 2017-12-27 Miles Q. Ott , Krista J. Gile , Matthew T. Harrison , Lisa G. Johnston , Joseph W. Hogan

Respondent-driven sampling (RDS) is a popular approach to study marginalized or hard-to-reach populations. It collects samples from a networked population by incentivizing participants to refer their friends into the study. One major…

Statistics Theory · Mathematics 2018-12-21 Yilin Zhang , Karl Rohe , Sebastien Roch

Surveys are critical inputs for research and policy, yet, enumerating a sampling frame is logistically infeasible or financially nonviable in many circumstances, such as during pandemics, natural disasters, or armed conflict. Respondent…

Applications · Statistics 2026-03-03 Adam Visokay , Laura Boudreau , Rachel M. Heath , Tyler H. McCormick