Ranked set sampling: its essence and some new applications

Chen, Zehua

doi:10.1007/s10651-007-0025-0

Cited by 35 publications

(14 citation statements)

References 34 publications

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“…However, researchers continue to work on alternative RSS schemes that are able to maintain the merits of conventional RSS without excluding any patients. In particular, Chen () discussed the use of extreme RSS (Samawi et al., 1996) for QTL mapping in genetics (Chen et al., ) and a modified RSS procedure for applications in clinical trials (Ozturk and MacEachern, ; Chenl et al., ).…”

Section: Motivation and Background Behind Rssmentioning

confidence: 99%

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Improved nonparametric estimation of the optimal diagnostic cut‐off point associated with the Youden index under different sampling schemes

2016

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A diagnostic cut-off point of a biomarker measurement is needed for classifying a random subject to be either diseased or healthy. However, the cut-off point is usually unknown and needs to be estimated by some optimization criteria. One important criterion is the Youden index, which has been widely adopted in practice. The Youden index, which is defined as the maximum of (sensitivity + specificity -1), directly measures the largest total diagnostic accuracy a biomarker can achieve. Therefore, it is desirable to estimate the optimal cut-off point associated with the Youden index. Sometimes, taking the actual measurements of a biomarker is very difficult and expensive, while ranking them without the actual measurement can be relatively easy. In such cases, ranked set sampling can give more precise estimation than simple random sampling, as ranked set samples are more likely to span the full range of the population. In this study, kernel density estimation is utilized to numerically solve for an estimate of the optimal cut-off point. The asymptotic distributions of the kernel estimators based on two sampling schemes are derived analytically and we prove that the estimators based on ranked set sampling are relatively more efficient than that of simple random sampling and both estimators are asymptotically unbiased. Furthermore, the asymptotic confidence intervals are derived. Intensive simulations are carried out to compare the proposed method using ranked set sampling with simple random sampling, with the proposed method outperforming simple random sampling in all cases. A real data set is analyzed for illustrating the proposed method.

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Section: Motivation and Background Behind Rssmentioning

confidence: 99%

“…The initial use of the RSS technique was proposed by McIntyre () and many of its early applications were in the field of agriculture. For more recent reviews and new applications of RSS; see Chen () and Wolfe (). For theories and more detailed discussions about RSS; see Dell and Clutter (); Wolfe (); and Chen et al.…”

Section: Introductionmentioning

confidence: 99%

Improved nonparametric estimation of the optimal diagnostic cut‐off point associated with the Youden index under different sampling schemes

2016

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“…Samawi et al (1996) proposed extreme ranked set sample (ERSS). This ERSS has important applications in genetics for quantitative trait loci mapping (Chen, 2007). Bivariate RSS was introduced by Al-Saleh and Zheng (2002).…”

Section: Treatment Allocation Based On Ranked Auxiliary Variablementioning

confidence: 99%

Evaluating the efficiency of treatment comparison in crossover design by allocating subjects based on ranked auxiliary variable

Huang

Samawi

Vogel

et al. 2016

CSAM

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The validity of statistical inference depends on proper randomization methods. However, even with proper randomization, we can have imbalanced with respect to important characteristics. In this paper, we introduce a method based on ranked auxiliary variables for treatment allocation in crossover designs using Latin squares models. We evaluate the improvement of the efficiency in treatment comparisons using the proposed method. Our simulation study reveals that our proposed method provides a more powerful test compared to simple randomization with the same sample size. The proposed method is illustrated by conducting an experiment to compare two different concentrations of titanium dioxide nanofiber (TDNF) on rats for the purpose of comparing weight gain.

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“…For a detailed review and bibliography on RSS, see Patil (1995) and Kaur et al (1995). For some real applications of RSS, see Yu and Lam (1997), Al-Saleh and Al-Shrafat (2001), Al-Saleh and Al-Hadrami (2003), Al-Saleh and Al-Omari (2002), Husby et al (2005), Chen (2007), Wang et al (2009), Ozturk (2011), Samawi (2011) and references therein.…”

Section: Introductionmentioning

confidence: 99%

Partial ranked set sampling design

et al. 2013

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In many environmental studies, the main focus is on observational economy, that is, to obtain data on the basis of cost‐effective and efficient sampling methods. In this paper, we propose a partial ranked set sampling (PRSS) method for estimation of population mean, median and variance. On the basis of perfect and imperfect rankings, Monte Carlo simulations from symmetric and asymmetric distributions are used to evaluate the effectiveness of the proposed estimators. It is found that the estimators under PRSS are more efficient than the estimators based on simple random sampling. The procedure is illustrated with a case study using a real data set. Copyright © 2013 John Wiley & Sons, Ltd.

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Ranked set sampling: its essence and some new applications

Cited by 35 publications

References 34 publications

Improved nonparametric estimation of the optimal diagnostic cut‐off point associated with the Youden index under different sampling schemes

Improved nonparametric estimation of the optimal diagnostic cut‐off point associated with the Youden index under different sampling schemes

Evaluating the efficiency of treatment comparison in crossover design by allocating subjects based on ranked auxiliary variable

Partial ranked set sampling design

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