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Related papers: Design-adherent estimators for network surveys

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Network sampling is used around the world for surveys of vulnerable, hard-to-reach populations including people at risk for HIV, opioid misuse, and emerging epidemics. The sampling methods include tracing social links to add new people to…

Methodology · Statistics 2020-02-05 Steve Thompson

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 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

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

Although the interest in the the use of social and information networks has grown, most inferences on networks assume the data collected represents the complete. However, when ignoring missing data, even when missing completely at random,…

Methodology · Statistics 2022-03-25 Tyler Vu , Tuo Lin , Jingjing Zou , Vladimir Novitsky , Xin Tu , Victor De Gruttola

Consider a population of individuals and a network that encodes social connections among them. We are interested in making inference on finite population and super-population estimands that are a function of both individuals' responses and…

Methodology · Statistics 2016-12-13 Simon Lunagomez , Edoardo Airoldi

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…

Methodology · Statistics 2016-10-24 Ashton M. Verdery , Jacob C. Fisher , Nalyn Siripong , Kahina Abdesselam , Shawn Bauldry

The use of big data in official statistics and the applied sciences is accelerating, but statistics computed using only big data often suffer from substantial selection bias. This leads to inaccurate estimation and invalid statistical…

Methodology · Statistics 2023-08-11 Ryan Covey , Lucca Buonamano

Intuitively, sampling is likely to be more efficient for prevalence estimation, if the cases (or positives) have a relatively higher representation in the sample than in the population. In case the virus is transmitted via personal…

Applications · Statistics 2020-11-18 Li-Chun Zhang

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

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

Partially-observed data collected by sampling methods is often being studied to obtain the characteristics of information diffusion networks. However, these methods usually do not consider the behavior of diffusion process. In this paper,…

Social and Information Networks · Computer Science 2014-05-30 Motahareh Eslami Mehdiabadi , Hamid R. Rabiee , Mostafa Salehi

Longitudinal cohorts to determine the incidence of HIV infection are logistically challenging, so researchers have sought alternative strategies. Recency test methods use biomarker profiles of HIV-infected subjects in a cross-sectional…

Methodology · Statistics 2022-01-13 Fei Gao , Marlena S. Bannick

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…

Applications · Statistics 2012-01-10 Xin Lu , Linus Bengtsson , Tom Britton , Martin Camitz , Beom Jun Kim , Anna Thorson , Fredrik Liljeros

Ending the HIV/AIDS pandemic is among the Sustainable Development Goals for the next decade. In order to overcome the gap between the need for care and the available resources, better understanding of HIV epidemics is needed to guide policy…

Applications · Statistics 2020-09-03 Zhou Lan , Le Bao

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

Cross-sectional HIV incidence estimation leverages recency test results to determine the HIV incidence of a population of interest, where recency test uses biomarker profiles to infer whether an HIV-positive individual was "recently"…

Methodology · Statistics 2023-11-21 Qi Wang , Ann Duerr , Fei Gao

Cross-sectional incidence estimation based on recency testing has become a widely used tool in HIV research. Recently, this method has gained prominence in HIV prevention trials to estimate the "placebo" incidence that participants might…

Methodology · Statistics 2024-12-18 Jianan Pan , Marlena Bannick , Fei Gao

Respondent-Driven Sampling (RDS) employs a variant of a link-tracing network sampling strategy to collect data from hard-to-reach populations. By tracing the links in the underlying social network, the process exploits the social structure…

Applications · Statistics 2009-04-14 Krista J. Gile , Mark S. Handcock

Increasing nonresponse rates and the cost of data collection are two pressing problems encountered in traditional probability surveys. The proliferation of inexpensive data from web surveys stimulates interest in statistical techniques for…

Methodology · Statistics 2019-12-31 Vladislav Beresovsky
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