Stratified Extreme Ranked Set Sample with Application to Ratio Estimators

Hani M. Samawi; Laith J. Saeid; Hani Samawi

doi:10.22237/jmasm/1083370320

Stratified Extreme Ranked Set Sample with Application to Ratio Estimators

Hani M. Samawi, Laith J. Saeid, Hani Samawi

Biostatistics, Epidemiology, & Environmental Health Sciences

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS). In some cases it is more efficient than ranked set sample (RSS) and stratified ranked set sample (SRSS), when the underlying distribution is symmetric. An application to real data on the bilirubin level in jaundice babies is introduced to illustrate the method.

Original language	American English
Journal	Journal of Modern Applied Statistical Methods
Volume	3
DOIs	https://doi.org/10.22237/jmasm/1083370320
State	Published - 2004

Keywords

Ratio estimators
Stratified extreme ranked set sample

DC Disciplines

Biostatistics

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title = "Stratified Extreme Ranked Set Sample with Application to Ratio Estimators",

abstract = " Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS). In some cases it is more efficient than ranked set sample (RSS) and stratified ranked set sample (SRSS), when the underlying distribution is symmetric. An application to real data on the bilirubin level in jaundice babies is introduced to illustrate the method.",

keywords = "Ratio estimators, Stratified extreme ranked set sample",

author = "Samawi, {Hani M.} and Saeid, {Laith J.} and Hani Samawi",

note = "Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS).",

year = "2004",

doi = "10.22237/jmasm/1083370320",

language = "American English",

volume = "3",

journal = "Journal of Modern Applied Statistical Methods",

issn = "1538-9472",

publisher = "Wayne State University",

}

TY - JOUR

T1 - Stratified Extreme Ranked Set Sample with Application to Ratio Estimators

AU - Samawi, Hani M.

AU - Saeid, Laith J.

AU - Samawi, Hani

N1 - Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS).

PY - 2004

Y1 - 2004

N2 - Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS). In some cases it is more efficient than ranked set sample (RSS) and stratified ranked set sample (SRSS), when the underlying distribution is symmetric. An application to real data on the bilirubin level in jaundice babies is introduced to illustrate the method.

AB - Stratified extreme ranked set sample (SERSS) is introduced. The performance of the combined and separate ratio estimates using SERSS is investigated. Theoretical and simulation study are presented. Results indicate that using SERSS for estimating the ratios is more efficient than using stratified simple random sample (SSRS) and simple random sample (SRS). In some cases it is more efficient than ranked set sample (RSS) and stratified ranked set sample (SRSS), when the underlying distribution is symmetric. An application to real data on the bilirubin level in jaundice babies is introduced to illustrate the method.

KW - Ratio estimators

KW - Stratified extreme ranked set sample

UR - https://doi.org/10.22237/jmasm/1083370320

U2 - 10.22237/jmasm/1083370320

DO - 10.22237/jmasm/1083370320

M3 - Article

SN - 1538-9472

VL - 3

JO - Journal of Modern Applied Statistical Methods

JF - Journal of Modern Applied Statistical Methods

ER -

Stratified Extreme Ranked Set Sample with Application to Ratio Estimators

Abstract

Keywords

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