Sampling and Estimation in Hidden Population Using Social Network

@article{Zhao2017SamplingAE,
  title={Sampling and Estimation in Hidden Population Using Social Network},
  author={Yang Zhao},
  journal={Journal of AIDS and Clinical Research},
  year={2017},
  volume={8},
  pages={1-3}
}
  • Yang Zhao
  • Published 27 February 2017
  • Mathematics
  • Journal of AIDS and Clinical Research
Characteristics of hidden populations (e.g. population of injection drug users) cannot be studied using standard sampling and estimation procedures. This article considers methods for estimating the population proportion of hidden population using social network. We compare the sampling and estimation technique of respondent-driven sampling with the simplified sampling procedure based on Markov-chain model and discusses the equivalence of these procedures. These procedures fail to provide… 

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References

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TLDR
This paper develops a sampling and estimation technique called respondent-driven sampling, which allows researchers to make asymptotically unbiased estimates about the characteristics of hidden populations such as injection drug users, the homeless, and artists.

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TLDR
A new variant of chain-referral sampling, respondent-driven sampling, is introduced that employs a dual system of structured incentives to overcome some of the deficiencies of such samples and discusses how respondent- driven sampling can improve both network sampling and ethnographic investigation.

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TLDR
The authors describe a venue-based application of time-space sampling (TSS) that addresses the challenges of accessing hard-to-reach populations and uses it in the ongoing Community Intervention Trial for Youth (CITY) project to generate a systematic sample of young men who have sex with men.

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This article describes a sampling and estimation scheme for estimating the size of an injecting drug user (IDU) population by combining classical sampling and respondent-driven sampling procedures.