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An Extensive and Comprehensive Review on RDS: Techniques, Applications and Problems

Mihir Bhatta, Agniva Majumdar, Piyali Ghosh, Debjit Chakraborty, Shanta Dutta

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Indian Journal of Biology 11(1):p 7-13, January - June 2024. | DOI: https://doi.org/10.21088/ijb.2394.1391.11124.1

How Cite This Article:

Bhatta M, Majumdar A, Ghosh P, et al. An Extensive and Comprehensive Review on RDS: Techniques, Applications and Problems. Indian J Biol. 2024;11(1):7-13.

Timeline

Received : March 29, 2024         Accepted : May 16, 2024          Published : June 09, 2024

Abstract

Respondent Driven Sampling (RDS) is becoming a widely used method to sample hardto-reach populations, especially in Public Health and Social Science research. The purpose of this systematic review is to present an overall view of RDS methodology, its applications in different areas as well as the difficulties faced when implementing it. A search of electronic databases was conducted systematically to find relevant studies for synthesis that would provide insight into the strengths, limitations and future directions of RDS.


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Data Sharing Statement

There are no additional data available.

Funding

This research received no funding.

Author Contributions

All authors contributed significantly to the work and approve its publication.

Ethics Declaration

This article does not involve any human or animal subjects, and therefore does not require ethics approval.

Acknowledgements

Information not provide.

Conflicts of Interest

The authors report no conflicts of interest in this work.


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Cite this article

Bhatta M, Majumdar A, Ghosh P, et al. An Extensive and Comprehensive Review on RDS: Techniques, Applications and Problems. Indian J Biol. 2024;11(1):7-13.


Licence:

Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)

This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.



Received Accepted Published
March 29, 2024 May 16, 2024 June 09, 2024

DOI: https://doi.org/10.21088/ijb.2394.1391.11124.1

Keywords

Respondent-Driven SamplingRDS MethodologyHidden PopulationsEpidemiologySocial ScienceSampling BiasNetwork Analysis

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Received March 29, 2024
Accepted May 16, 2024
Published June 09, 2024

licence


Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)

This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.



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