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Sensitive proportion in ranked set sampling

This paper considers the concomitant-based rank set sampling (CRSS) for estimation of the sensitive proportion. It is shown that CRSS procedure provides an unbiased estimator of the population sensitive proportion, and it is always more precise than corresponding sample sensitive proportion (Warner...

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Detalles Bibliográficos
Autores principales: Abbasi, Azhar Mehmood, Shad, Muhammad Yousaf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407548/
https://www.ncbi.nlm.nih.gov/pubmed/34464414
http://dx.doi.org/10.1371/journal.pone.0256699
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author Abbasi, Azhar Mehmood
Shad, Muhammad Yousaf
author_facet Abbasi, Azhar Mehmood
Shad, Muhammad Yousaf
author_sort Abbasi, Azhar Mehmood
collection PubMed
description This paper considers the concomitant-based rank set sampling (CRSS) for estimation of the sensitive proportion. It is shown that CRSS procedure provides an unbiased estimator of the population sensitive proportion, and it is always more precise than corresponding sample sensitive proportion (Warner SL (1965)) that based on simple random sampling (SRS) without increasing sampling cost. Additionally, a new estimator based on ratio method is introduced using CRSS protocol, preserving the respondent’s confidentiality through a randomizing device. The numerical results of these estimators are obtained by using numerical integration technique. An application to real data is also given to support the methods.
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spelling pubmed-84075482021-09-01 Sensitive proportion in ranked set sampling Abbasi, Azhar Mehmood Shad, Muhammad Yousaf PLoS One Research Article This paper considers the concomitant-based rank set sampling (CRSS) for estimation of the sensitive proportion. It is shown that CRSS procedure provides an unbiased estimator of the population sensitive proportion, and it is always more precise than corresponding sample sensitive proportion (Warner SL (1965)) that based on simple random sampling (SRS) without increasing sampling cost. Additionally, a new estimator based on ratio method is introduced using CRSS protocol, preserving the respondent’s confidentiality through a randomizing device. The numerical results of these estimators are obtained by using numerical integration technique. An application to real data is also given to support the methods. Public Library of Science 2021-08-31 /pmc/articles/PMC8407548/ /pubmed/34464414 http://dx.doi.org/10.1371/journal.pone.0256699 Text en © 2021 Abbasi, Shad https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Abbasi, Azhar Mehmood
Shad, Muhammad Yousaf
Sensitive proportion in ranked set sampling
title Sensitive proportion in ranked set sampling
title_full Sensitive proportion in ranked set sampling
title_fullStr Sensitive proportion in ranked set sampling
title_full_unstemmed Sensitive proportion in ranked set sampling
title_short Sensitive proportion in ranked set sampling
title_sort sensitive proportion in ranked set sampling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407548/
https://www.ncbi.nlm.nih.gov/pubmed/34464414
http://dx.doi.org/10.1371/journal.pone.0256699
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