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Respondent-Driven Sampling (RDS) is a chain-referral design used for collecting data from hidden or hard-to-reach populations through their social networks. In RDS, respondents recruit their peers from the population of interest. As such,…

Methodology · Statistics 2026-04-14 Vanesa Reinoso , Danilo Alvares , Jonathan Acosta , Isabelle S. Beaudry

Respondent-driven sampling (RDS) is a link-tracing procedure for surveying hidden or hard-to-reach populations in which subjects recruit other subjects via their social network. There is significant research interest in detecting clustering…

Applications · Statistics 2015-11-18 Forrest W. Crawford , Peter M. Aronow , Li Zeng , Jianghong Li

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 variant of link-tracing, a sampling technique for surveying hard-to-reach communities that takes advantage of community members' social networks to reach potential participants. As a network-based…

Respondent-driven sampling (RDS) is both a sampling strategy and an estimation method. It is commonly used to study individuals that are difficult to access with standard sampling techniques. As with any sampling strategy, RDS has…

Applications · Statistics 2023-09-29 Jessica P. Kunke , Adam Visokay , Tyler H. McCormick

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

Respondent-driven sampling (RDS) is an approach to sampling design and analysis which utilizes the networks of social relationships that connect members of the target population, using chain-referral methods to facilitate sampling. RDS…

Methodology · Statistics 2015-08-19 Yakir Berchenko , Jonathan Rosenblatt , Simon D. W. Frost

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…

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

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation…

Applications · Statistics 2016-11-14 Dennis M. Feehan , Matthew J. Salganik

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…

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

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…

Methodology · Statistics 2010-06-25 Krista J. Gile

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

There is great interest in finding meaningful subgroups of attributed network data. There are many available methods for clustering complete network. Unfortunately, much network data is collected through sampling, and therefore incomplete.…

Social and Information Networks · Computer Science 2020-08-11 Shuaimin Kang , Krista Gile , Pedro Mateu-Gelabert , Honoria Guarino

This paper presents a method for estimating the overall size of a hidden population using results from a respondent driven sampling (RDS) survey. We use data from the Latino MSM Community Involvement survey (LMSM-CI), an RDS dataset that…

Social and Information Networks · Computer Science 2021-12-22 Nicholas Budzban , Katherine Silverio , John Matta

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

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

The discovery of the "hidden population", whose size and membership are unknown, is made possible by assuming that its members are connected in a social network by their relationships. We explore these groups by a chain-referral sampling…

Probability · Mathematics 2020-05-21 Thi Phuong Thuy Vo

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