Using ranked set sampling with extreme ranks in estimating the population proportion

Zamanzade, Ehsan; Mahdizadeh, M.

doi:10.1177/0962280218823793

Cited by 49 publications

(16 citation statements)

References 29 publications

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“…The ranked set sampling (RSS) design, as an alternative design to the two-phase sampling designs, has been proposed by McIntyre 36 and has received increasing attention. Recently, Zamanzade and Vock 37 showed that the RSS design is more efficient than the two-phase sampling designs under certain cases, and Zamanzade and Mahdizadeh 38 used a variation of RSS to efficiently estimate the prevalence of a rare disease in a given population. It is of interest to extend our work to RSS-based designs for constructing risk scores and assessing absolute risks simultaneously for future research.…”

Section: Discussionmentioning

confidence: 99%

Semiparametric isotonic regression analysis for risk assessment under nested case-control and case-cohort designs

Feng

et al. 2019

Stat Methods Med Res

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Two-phase sampling designs, including nested case-control and case-cohort designs, are frequently utilized in large cohort studies involving expensive biomarkers. To analyze data from two-phase designs with a binary outcome, parametric models such as logistic regression are often adopted. However, when the model assumptions are not valid, parametric models may lead to biased estimation and risk evaluation. In this paper, we propose a robust semiparametric regression model for binary outcomes and an easy-to-implement computational procedure that combines the pool-adjacent violators algorithm with inverse probability weighting. The asymptotic properties are established, including consistency and the convergence rate. Simulation studies show that the proposed method performs well and is more robust than logistic regression methods. We demonstrate the application of the proposed method to real data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial.

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Section: Discussionmentioning

confidence: 99%

Semiparametric isotonic regression analysis for risk assessment under nested case-control and case-cohort designs

Feng

et al. 2019

Stat Methods Med Res

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“…RSS designs assume that there will be no errors in ranking the units with respect to the variable of interest. Al-Omari and Al-Hadhrami (2011) and Zamanzade and Mahdizadeh (2020) discussed this statement and found that for most practical applications there will imperfectly ranking and there will be a loss in efficiency of the estimators based on RSS. To reduce the errors in ranking, several modifications on the RSS procedure were made.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Exponential Pareto Distribution’s Parameters under Ranked and Double Ranked Set Sampling Designs

Sabry

Almetwally

2021

Pak.j.stat.oper.res.

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In this paper, the derivation of the likelihood function for parameter estimation based on double ranked set sampling (DRSS) designs used by Sabry el.al.; (2019) for the estimation of the parameters of the power generalized Weibull distribution is considered. The developed likelihood function is then used for the estimation of the exponential Pareto distribution parameters. The maximum likelihood estimators (MLEs) are then investigated and compared to the corresponding ones based on simple random sampling (SRS) and ranked set sampling (RSS) designs. A Monte Carlo simulation is conducted and the absolute relative biases, mean square errors, and efficiencies are compared for the different designs. The relative efficiency of the DRSS estimates with respect to other designs was found to be higher in case of the exponential Pareto distribution (EP).

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“…Al-Omari [4] investigated the mean estimation using modified robust extreme ranked set sampling method. Zamanzade and Mahdizadeh [27] used the ranked set sampling method with extreme ranks in estimating the population proportion. Al-Omari et al [8] studied the estimation of the stress-strength reliability for exponentiated Pareto distribution using median and ranked set sampling methods.…”

Section: Introductionmentioning

confidence: 99%

Maximum likelihood estimation in location-scale families using varied L ranked set sampling

Al-Omari

2021

RAIRO-Oper. Res.

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Recently, a generalized ranked set sampling (RSS) scheme has been introduced which encompasses several existing RSS schemes, namely varied L RSS (VLRSS), and it provides more precise estimators of the population mean than the estimators with the traditional simple random sampling (SRS) and RSS schemes. In this paper, we extend the work and consider the maximum likelihood estimators (MLEs) of the location and scale parameters when sampling from a location-scale family of distributions. In order to give more insight into the performance of VLRSS with respect to SRS and RSS schemes, the asymptotic relative precisions of the MLEs using VLRSS relative to that using SRS and RSS are compared for some usual location-scale distributions. It turns out that the MLEs with VLRSS are more precise than those with the existing sampling schemes.

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Using ranked set sampling with extreme ranks in estimating the population proportion

Cited by 49 publications

References 29 publications

Semiparametric isotonic regression analysis for risk assessment under nested case-control and case-cohort designs

Semiparametric isotonic regression analysis for risk assessment under nested case-control and case-cohort designs

Estimation of the Exponential Pareto Distribution’s Parameters under Ranked and Double Ranked Set Sampling Designs

Maximum likelihood estimation in location-scale families using varied L ranked set sampling

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