Cargando…

On partial randomized response model using ranked set sampling

In this paper, we propose a partial randomized response technique to collect reliable sensitive data for estimation of population proportion in ranked set sampling (RSS) scheme using auxiliary information. The idea is to increase confidence and (or) co-operation of the respondents by providing them...

Descripción completa

Detalles Bibliográficos
Autores principales: Abbasi, Azhar Mehmood, Shad, Muhammad Yousaf, Ahmed, Aneel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707803/
https://www.ncbi.nlm.nih.gov/pubmed/36445862
http://dx.doi.org/10.1371/journal.pone.0277497
_version_ 1784840778921541632
author Abbasi, Azhar Mehmood
Shad, Muhammad Yousaf
Ahmed, Aneel
author_facet Abbasi, Azhar Mehmood
Shad, Muhammad Yousaf
Ahmed, Aneel
author_sort Abbasi, Azhar Mehmood
collection PubMed
description In this paper, we propose a partial randomized response technique to collect reliable sensitive data for estimation of population proportion in ranked set sampling (RSS) scheme using auxiliary information. The idea is to increase confidence and (or) co-operation of the respondents by providing them the option of both ‘direct’ and ‘randomized’ response for the inquired sensitive question. This option is quite logical because perception of sensitive (insensitive) inquiry can vary among respondents. The properties of the proposed method are discussed and compared with existing randomized response techniques. Cost analysis is also carried out to prove supremacy of the suggested method. Finally, an application to clinical trial on AIDS is included.
format Online
Article
Text
id pubmed-9707803
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-97078032022-11-30 On partial randomized response model using ranked set sampling Abbasi, Azhar Mehmood Shad, Muhammad Yousaf Ahmed, Aneel PLoS One Research Article In this paper, we propose a partial randomized response technique to collect reliable sensitive data for estimation of population proportion in ranked set sampling (RSS) scheme using auxiliary information. The idea is to increase confidence and (or) co-operation of the respondents by providing them the option of both ‘direct’ and ‘randomized’ response for the inquired sensitive question. This option is quite logical because perception of sensitive (insensitive) inquiry can vary among respondents. The properties of the proposed method are discussed and compared with existing randomized response techniques. Cost analysis is also carried out to prove supremacy of the suggested method. Finally, an application to clinical trial on AIDS is included. Public Library of Science 2022-11-29 /pmc/articles/PMC9707803/ /pubmed/36445862 http://dx.doi.org/10.1371/journal.pone.0277497 Text en © 2022 Abbasi 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
Abbasi, Azhar Mehmood
Shad, Muhammad Yousaf
Ahmed, Aneel
On partial randomized response model using ranked set sampling
title On partial randomized response model using ranked set sampling
title_full On partial randomized response model using ranked set sampling
title_fullStr On partial randomized response model using ranked set sampling
title_full_unstemmed On partial randomized response model using ranked set sampling
title_short On partial randomized response model using ranked set sampling
title_sort on partial randomized response model using ranked set sampling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707803/
https://www.ncbi.nlm.nih.gov/pubmed/36445862
http://dx.doi.org/10.1371/journal.pone.0277497
work_keys_str_mv AT abbasiazharmehmood onpartialrandomizedresponsemodelusingrankedsetsampling
AT shadmuhammadyousaf onpartialrandomizedresponsemodelusingrankedsetsampling
AT ahmedaneel onpartialrandomizedresponsemodelusingrankedsetsampling