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Partial stratified ranked set sampling scheme for estimation of population mean and median

Ranked set sampling is an alternative to simple random sampling, which uses the least amount of money and time. The ranked set sampling (RSS) is modified to obtain a more efficient and cost-effective estimator of population parameters. This paper aims to bring a more efficient and cost-effective des...

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Detalles Bibliográficos
Autores principales: M, Maria, Almanjahie, Ibrahim M., Ismail, Muhammad, Cheema, Ammara Nawaz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931123/
https://www.ncbi.nlm.nih.gov/pubmed/36791145
http://dx.doi.org/10.1371/journal.pone.0275340
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author M, Maria
Almanjahie, Ibrahim M.
Ismail, Muhammad
Cheema, Ammara Nawaz
author_facet M, Maria
Almanjahie, Ibrahim M.
Ismail, Muhammad
Cheema, Ammara Nawaz
author_sort M, Maria
collection PubMed
description Ranked set sampling is an alternative to simple random sampling, which uses the least amount of money and time. The ranked set sampling (RSS) is modified to obtain a more efficient and cost-effective estimator of population parameters. This paper aims to bring a more efficient and cost-effective design than stratified ranked set sampling and simple random sampling. In some distributions, the suggested method used fewer sample units than stratified ranked set sampling and gives a more efficient estimation of population parameters. In symmetric distributions, the proposed design, called "partial stratified ranked set sampling" yields an unbiased estimator of the population mean. The design is illustrated with practical data of COVID-19 confirmed cases.
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spelling pubmed-99311232023-02-16 Partial stratified ranked set sampling scheme for estimation of population mean and median M, Maria Almanjahie, Ibrahim M. Ismail, Muhammad Cheema, Ammara Nawaz PLoS One Research Article Ranked set sampling is an alternative to simple random sampling, which uses the least amount of money and time. The ranked set sampling (RSS) is modified to obtain a more efficient and cost-effective estimator of population parameters. This paper aims to bring a more efficient and cost-effective design than stratified ranked set sampling and simple random sampling. In some distributions, the suggested method used fewer sample units than stratified ranked set sampling and gives a more efficient estimation of population parameters. In symmetric distributions, the proposed design, called "partial stratified ranked set sampling" yields an unbiased estimator of the population mean. The design is illustrated with practical data of COVID-19 confirmed cases. Public Library of Science 2023-02-15 /pmc/articles/PMC9931123/ /pubmed/36791145 http://dx.doi.org/10.1371/journal.pone.0275340 Text en © 2023 M et al 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
M, Maria
Almanjahie, Ibrahim M.
Ismail, Muhammad
Cheema, Ammara Nawaz
Partial stratified ranked set sampling scheme for estimation of population mean and median
title Partial stratified ranked set sampling scheme for estimation of population mean and median
title_full Partial stratified ranked set sampling scheme for estimation of population mean and median
title_fullStr Partial stratified ranked set sampling scheme for estimation of population mean and median
title_full_unstemmed Partial stratified ranked set sampling scheme for estimation of population mean and median
title_short Partial stratified ranked set sampling scheme for estimation of population mean and median
title_sort partial stratified ranked set sampling scheme for estimation of population mean and median
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931123/
https://www.ncbi.nlm.nih.gov/pubmed/36791145
http://dx.doi.org/10.1371/journal.pone.0275340
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