The matched pair sign test using bivariate ranked set sampling for different ranking based schemes

Samawi, Hani M.; Al-Saleh, Mohammad Fraiwan; Al-Saidy, Obaid

doi:10.1016/j.stamet.2009.02.002

Cited by 11 publications

(4 citation statements)

References 34 publications

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“…We can indicate that several authors used the data presented in Table 1 to clarify some procedures for bivariate sign tests, for example, see Brown et al 9 . Data set 2 is a simple study of twelve cotton textile workers who were researched by Merchant et al 32 to determine the effects of cotton dust exposure. Before and after each participant’s 6-h exposure to cotton dust, several factors were measured for each worker, including the change in closing volume and white blood cell count.…”

Section: Illustrative Examples and Simulation Studiesmentioning

confidence: 99%

A new approach for approximating the p-value of a class of bivariate sign tests

Shanan,

Abd-Elfattah,

Abd El-Raheem

2023

Sci Rep

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Bivariate data are frequently encountered in many applied fields, including econometrics, engineering, physiology, biology, and medicine. For bivariate analysis, a wide range of non-parametric and parametric techniques can be applied. There are fewer requirements needed for non-parametric procedures than for parametric ones. In this paper, the saddlepoint approximation method is used to approximate the exact p-values of some non-parametric bivariate tests. The saddlepoint approximation is an approximation method used to approximate the mass or density function and the cumulative distribution function of a random variable based on its moment generating function. The saddlepoint approximation method is proposed in this article as an alternative to the asymptotic normal approximation. A comparison between the proposed method and the normal asymptotic approximation method is performed by conducting Monte Carlo simulation study and analyzing three numerical examples representing bivariate real data sets. In general, the results of the simulation study show the superiority of the proposed method over the asymptotic normal approximation method.

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Section: Illustrative Examples and Simulation Studiesmentioning

confidence: 99%

A new approach for approximating the p-value of a class of bivariate sign tests

Shanan,

Abd-Elfattah,

Abd El-Raheem

2023

Sci Rep

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“…Several authors have claimed that use of the auxiliary variable at the designing stage can result in more efficient estimates. For the applications of RSS in various disciplines of research, one can review the work of [19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

An efficient class of estimators for finite population mean in the presence of non-response under ranked set sampling (RSS)

Rehman

Shabbir

2022

PLoS ONE

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In this study, we address the problem of estimating the finite population mean when the non-response occurs on the characteristics under study. We propose a class of Rao-regression type estimators when ranked set sampling (RSS) procedure is used to collect the data from non-response group only and from both, the response and non-response groups. The information provided on the auxiliary variable is used at both stages i.e., at designing stage and the estimation stage. Expressions for bias and mean square error of the estimators are obtained up to first order of approximation. A comprehensive simulation study is carried out to observe the performances of the estimators under non-response.

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“…Takahasi and Wakimoto [37] established a rigorous statistical foundation for the theory of RSS. There is an extensive literature on this topic; see, for example, [4,8,10,11,15,25,30,31,33,34,39,40].…”

Section: Introductionmentioning

confidence: 99%

More efficient logistic analysis using moving extreme ranked set sampling

Samawi

Rochani

Linder

et al. 2016

Journal of Applied Statistics

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Logistic regression is the most popular technique available for modeling dichotomous-dependent variables. It has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient logistic regression analysis based on moving extreme ranked set sampling (MERSS min ) scheme with ranking based on an easy-to-available auxiliary variable known to be associated with the variable of interest (response variable). The paper demonstrates that this approach will provide more powerful testing procedure as well as more efficient odds ratio and parameter estimation than using simple random sample (SRS). Theoretical derivation and simulation studies will be provided.

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The matched pair sign test using bivariate ranked set sampling for different ranking based schemes

Cited by 11 publications

References 34 publications

A new approach for approximating the p-value of a class of bivariate sign tests

A new approach for approximating the p-value of a class of bivariate sign tests

An efficient class of estimators for finite population mean in the presence of non-response under ranked set sampling (RSS)

More efficient logistic analysis using moving extreme ranked set sampling

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