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Partial stratified ranked set sampling scheme for estimation of population mean and median.
M, Maria; Almanjahie, Ibrahim M; Ismail, Muhammad; Cheema, Ammara Nawaz.
  • M M; Department of Statistics, COMSATS University, Islamabad, Lahore, Pakistan.
  • Almanjahie IM; Department of Mathematics, College of Science, King Khalid University, Abha, Saudi Arabia.
  • Ismail M; Statistical Research and Studies Support Unit, King Khalid University, Abha, Saudi Arabia.
  • Cheema AN; Department of Statistics, COMSATS University, Islamabad, Lahore, Pakistan.
PLoS One ; 18(2): e0275340, 2023.
Article in English | MEDLINE | ID: covidwho-2243107
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0275340

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2023 Document Type: Article Affiliation country: Journal.pone.0275340