Estimating Odds Using Moving Extreme Ranked Set Sampling

Mohammad F. Al-Saleh; Hani Samawi

doi:10.1016/j.stamet.2009.11.004

Estimating Odds Using Moving Extreme Ranked Set Sampling

Mohammad F. Al-Saleh, Hani Samawi

Biostatistics, Epidemiology, & Environmental Health Sciences

Yarmouk University

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

19 Scopus citations

Abstract

In this paper, the estimation of the odds F / (1 - F) is considered based on Moving Extreme Ranked Set Sampling (MERSS), a variation of Ranked Set Sampling. The suggested estimator based on MERSS is motivated by some of the theoretical properties of the sum of geometric series. The new estimator and the naive estimator based on simple random sample (SRS) are compared via their mean squared errors. It turned out that the estimator based on MERSS is always valid and can have some advantages over that based on SRS. Data from a level I Trauma center are used to illustrate the procedures developed in this paper.

Original language	American English
Journal	Statistical Methodology
Volume	7
DOIs	https://doi.org/10.1016/j.stamet.2009.11.004
State	Published - Jan 1 2010

Keywords

Empirical Distribution
Odds
Odds Ratio Moving Extreme Ranked Set Sampling
Ranked Set Sampling

DC Disciplines

Public Health
Biostatistics
Community Health

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10.1016/j.stamet.2009.11.004License: Unspecified

http://dx.doi.org/10.1016/j.stamet.2009.11.004

Cite this

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title = "Estimating Odds Using Moving Extreme Ranked Set Sampling",

abstract = "In this paper, the estimation of the odds F / (1 - F) is considered based on Moving Extreme Ranked Set Sampling (MERSS), a variation of Ranked Set Sampling. The suggested estimator based on MERSS is motivated by some of the theoretical properties of the sum of geometric series. The new estimator and the naive estimator based on simple random sample (SRS) are compared via their mean squared errors. It turned out that the estimator based on MERSS is always valid and can have some advantages over that based on SRS. Data from a level I Trauma center are used to illustrate the procedures developed in this paper.",

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AU - Samawi, Hani

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N2 - In this paper, the estimation of the odds F / (1 - F) is considered based on Moving Extreme Ranked Set Sampling (MERSS), a variation of Ranked Set Sampling. The suggested estimator based on MERSS is motivated by some of the theoretical properties of the sum of geometric series. The new estimator and the naive estimator based on simple random sample (SRS) are compared via their mean squared errors. It turned out that the estimator based on MERSS is always valid and can have some advantages over that based on SRS. Data from a level I Trauma center are used to illustrate the procedures developed in this paper.

AB - In this paper, the estimation of the odds F / (1 - F) is considered based on Moving Extreme Ranked Set Sampling (MERSS), a variation of Ranked Set Sampling. The suggested estimator based on MERSS is motivated by some of the theoretical properties of the sum of geometric series. The new estimator and the naive estimator based on simple random sample (SRS) are compared via their mean squared errors. It turned out that the estimator based on MERSS is always valid and can have some advantages over that based on SRS. Data from a level I Trauma center are used to illustrate the procedures developed in this paper.

KW - Empirical Distribution

KW - Odds

KW - Odds Ratio Moving Extreme Ranked Set Sampling

KW - Ranked Set Sampling

UR - https://digitalcommons.georgiasouthern.edu/biostat-facpubs/9

UR - http://dx.doi.org/10.1016/j.stamet.2009.11.004

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DO - 10.1016/j.stamet.2009.11.004

M3 - Article

SN - 1572-3127

VL - 7

JO - Statistical Methodology

JF - Statistical Methodology

ER -

Estimating Odds Using Moving Extreme Ranked Set Sampling

Abstract

Keywords

DC Disciplines

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