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Ranked Set Sampling

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Ranked Set Sampling

Ranked Set Sampling Book
Author : Zehua Chen,Zhidong Bai,Bimal Sinha
Publisher : Springer Science & Business Media
Release : 2013-03-09
ISBN : 0387216642
Language : En, Es, Fr & De

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Book Description :

The first book on the concept and applications of ranked set sampling. It provides a comprehensive review of the literature, and it includes many new results and novel applications. The detailed description of various methods illustrated by real or simulated data makes it useful for scientists and practitioners in application areas such as agriculture, forestry, sociology, ecological and environmental science, and medical studies. It can serve as a reference book and as a textbook for a short course at the graduate level.

Handling Missing Data in Ranked Set Sampling

Handling Missing Data in Ranked Set Sampling Book
Author : Carlos N. Bouza-Herrera
Publisher : Springer Science & Business Media
Release : 2013-10-04
ISBN : 3642398995
Language : En, Es, Fr & De

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Book Description :

​The existence of missing observations is a very important aspect to be considered in the application of survey sampling, for example. In human populations they may be caused by a refusal of some interviewees to give the true value for the variable of interest. Traditionally, simple random sampling is used to select samples. Most statistical models are supported by the use of samples selected by means of this design. In recent decades, an alternative design has started being used, which, in many cases, shows an improvement in terms of accuracy compared with traditional sampling. It is called Ranked Set Sampling (RSS). A random selection is made with the replacement of samples, which are ordered (ranked). The literature on the subject is increasing due to the potentialities of RSS for deriving more effective alternatives to well-established statistical models. In this work, the use of RSS sub-sampling for obtaining information among the non respondents and different imputation procedures are considered. RSS models are developed as counterparts of well-known simple random sampling (SRS) models. SRS and RSS models for estimating the population using missing data are presented and compared both theoretically and using numerical experiments.

Ranked Set Sampling

Ranked Set Sampling Book
Author : Carlos N. Bouza-Herrera,Amer Ibrahim Falah Al-Omari
Publisher : Academic Press
Release : 2018-10-16
ISBN : 0128156937
Language : En, Es, Fr & De

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Book Description :

Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a good representation of the population and minimizes the costs associated with obtaining them. The main focus of many agricultural, ecological and environmental studies is the development of well designed, cost-effective and efficient sampling designs, giving RSS techniques a particular place in resolving the disciplinary problems of economists in application contexts, particularly experimental economics. This book seeks to place RSS at the heart of economic study designs. Focuses on how researchers should manipulate RSS techniques for specific applications Discusses RSS performs in popular statistical models, such as regression and hypothesis testing Includes a discussion of open theoretical research problems Provides mathematical proofs, enabling researchers to develop new models

Ranked Set Sampling

Ranked Set Sampling Book
Author : Munir Ahmad,M. Hanif,Hassen A. Muttlak
Publisher : Cambridge Scholars Publishing
Release : 2010-09-13
ISBN : 1443825220
Language : En, Es, Fr & De

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Book Description :

Ranked Set Sampling is one of the new areas of study in this region of the world and is a growing subject of research. Recently, researchers have paid attention to the development of the types of sampling; though it was not welcome in the beginning, it has numerous advantages over the classical sampling techniques. Ranked Set Sampling is doubly random and can be used in any survey designs. The Pakistan Journal of Statistics had attracted statisticians and samplers around the world to write up aspects of Ranked Set Sampling. All of the essays in this book have been reviewed by many critics. This volume can be used as a reference book for postgraduate students in economics, social sciences, medical and biological sciences, and statistics. The subject is still a hot topic for MPhil and PhD students for their dissertations.

The Efficiency of Improved Ranked Set Sampling Methods

The Efficiency of Improved Ranked Set Sampling Methods Book
Author : Syed Shahadat Hossain
Publisher : Unknown
Release : 1999
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Ranked set sampling is a desirable sampling technique where the ranking of the sample observations does not require the actual measurement. This thesis develops new ranked set sampling techniques and determines the sampling characteristics required to best estimate the required population parameters, such as mean and variance.

Ranked Set Sampling Models and Methods

Ranked Set Sampling Models and Methods Book
Author : Carlos Narciso Bouza Herrera
Publisher : Unknown
Release : 2021
ISBN : 9781799875567
Language : En, Es, Fr & De

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Book Description :

When it comes to data collection and analysis, ranked set sampling (RSS) continues to increasingly be the focus of methodological research. This type of sampling is an alternative to simple random sampling and can offer substantial improvements in precision and efficient estimation. There are different methods within RSS that can be further explored and discussed. On top of being efficient, RSS is cost-efficient and can be used in situations where sample units are difficult to obtain. With new results in modeling and applications, and a growing importance in theory and practice, it is essential for modeling to be further explored and developed through research. Ranked Set Sampling Models and Methods presents an innovative look at modeling survey sampling research and new models of RSS along with the future potentials of it. The book provides a panoramic view of the state of the art of RSS by presenting some previously known and new models. The chapters illustrate how the modeling is to be developed and how they improve the efficiency of the inferences. The chapters highlight topics such as bootstrap methods, fuzzy weight ranked set sampling method, item count technique, stratified ranked set sampling, and more. This book is essential for statisticians, social and natural science scientists, physicians and all the persons involved with the use of sampling theory in their research along with practitioners, researchers, academicians, and students interested in the latest models and methods for ranked set sampling.

Ranked Set Sampling Techniques Useful in Environmental Monitoring

Ranked Set Sampling Techniques Useful in Environmental Monitoring Book
Author : Girja Shankar Pandey,Neeraj Tiwari
Publisher : LAP Lambert Academic Publishing
Release : 2012-07
ISBN : 9783659181528
Language : En, Es, Fr & De

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Book Description :

Ranked set sampling (RSS)is a novel method of achieving observational economy compared to Simple random sampling (SRS. Often we are faced with situations where measurements on the actual variable are costly and time consuming. However, if we can rank the items by mere inspection, according to the variable without taking actual measurements, this often happens in environmental monitoring and assessment that require observational data.In this book we obtain the utility of ranked set sampling over the simple random sampling with the help of numerical illustrations. In the next chapter of the book we have proposed an adaptive cluster sampling theory based on ranked sets.

Advanced Ranked Set Sampling Theory with Auxiliary Information

Advanced Ranked Set Sampling Theory with Auxiliary Information Book
Author : Mehta Nitu
Publisher : LAP Lambert Academic Publishing
Release : 2015-07-27
ISBN : 9783659755446
Language : En, Es, Fr & De

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Book Description :

The speciality of ranked set sampling is that it combines simple random sampling with other sources of information such as professional knowledge, auxiliary information, judgement, etc., which are inexpensive and easily obtained. In this study, the problem of estimating the unknown population mean of the study variable using information on auxiliary variable has been considered and new estimators have been developed with their properties in ranked set sampling and stratified ranked set sampling. Use of auxiliary information has been in practice for improving the efficiencies of the estimators of population parameters. Formulation of estimators for population mean using auxiliary information in ranked set sampling and stratified ranked set sampling has been main objective of the present investigation. Some empirical studies are also given in the support of theoretical findings.

Handling Missing Data in Ranked Set Sampling

Handling Missing Data in Ranked Set Sampling Book
Author : Carlos N. Bouza-Herrera
Publisher : Unknown
Release : 2013-10-31
ISBN : 9783642399008
Language : En, Es, Fr & De

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Book Description :

Download Handling Missing Data in Ranked Set Sampling book written by Carlos N. Bouza-Herrera, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

On Estimation of Population Variance Based on a Ranked Set Sampling

On Estimation of Population Variance Based on a Ranked Set Sampling Book
Author : Sukuman Sarikavanij,Mahāwitthayālai Mahidon,Mahāwitthayālai Mahidon. Khana Witthayāsāt
Publisher : Unknown
Release : 2002
ISBN : 9789740414056
Language : En, Es, Fr & De

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Book Description :

Download On Estimation of Population Variance Based on a Ranked Set Sampling book written by Sukuman Sarikavanij,Mahāwitthayālai Mahidon,Mahāwitthayālai Mahidon. Khana Witthayāsāt, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Minimum Disparity Inference for Discrete Ranked Set Sampling Data

Minimum Disparity Inference for Discrete Ranked Set Sampling Data Book
Author : Roxana Antoanela Alexandridis
Publisher : Unknown
Release : 2005
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Abstract: Ranked set sampling (RSS) is a sampling scheme which can successfully replace simple random sampling (SRS) in experimental settings where measuring the units of interest is difficult, expensive, or time consuming, but ranking small subsets of units is relatively easy and inexpensive. Under perfect ranking, the statistical inference based on a RSS data is more efficient than the inference based on a SRS data of equal size. In practice, the ranking process is most likely subject to errors, and the efficiency of the inference decreases with the decrease in the quality of the ranking procedure. Thus, the central issue of a parametric inference is to balance the two ideals: efficiency when the ranking is perfect, and robustness when the ranking is imperfect. Typically there is a trade-off between these two ideals. In order to address this issue, we develop robust statistical inference based on a RSS data from a family of discrete distributions. Our inference relies on minimum disparity functions that measure the distance between the empirical and model distributions. We develop a class of estimators obtained by minimizing disparities between the assumed and empirical models. We show that all minimum disparity estimators are asymptotically efficient at the correct model under perfect ranking. We also show that there exists an estimator within this class, the minimum Hellinger distance estimator, that produces substantially smaller bias than the bias of the maximum likelihood estimator under imperfect ranking. In addition to robust estimation, we also developed a class of testing procedures, referred to as disparity deviance tests, to test certain hypotheses about the parameters of a family of discrete distributions. We show that under perfect ranking, the disparity deviance tests have the same asymptotic null distribution as the likelihood ratio test. Furthermore, we show that the disparity deviance test based on the Hellinger distance is more stable to imperfect ranking than the likelihood ratio test. We provide finite sample simulation results to evaluate the performance of the proposed procedures.

Ranked Set Sampling for Binary and Ordered Categorical Variables with Applications in Health Survey Data

Ranked Set Sampling for Binary and Ordered Categorical Variables with Applications in Health Survey Data Book
Author : Haiying Chen
Publisher : Unknown
Release : 2004
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Abstract: Ranked set sampling (RSS) is a sampling procedure that can be considerably more efficient than simple random sampling. It involves preliminary ranking of the variable of interest to aid in sample selection. Although ranking processes for continuous variables have been studied extensively in the literature, the use of RSS in the case of a binary variable has not been investigated thoroughly. We investigate the application of RSS to estimation of a population proportion theoretically and empirically using a National Health and Nutrition Examination Survey III (NHANES III) data set. We propose the use of logistic regression to aid in the ranking of the binary variable of interest. Our results indicate that this use of logistic regression leads to substantial gains in precision for estimation of a population proportion. Further, we illustrate how data from one source can be used to construct the necessary logistic regression equation, which can, in turn, be used to estimate the relevant proportions in a second group of subjects for which the same predictor variables are available. The results indicate the extent to which the sample size required to achieve a desired precision is reduced. Balanced RSS, however, is not in general optimal in terms of variance reduction. We investigate the application of unbalanced RSS to estimation of a population proportion. In particular, Neyman allocation is shown to be optimal for this setting. Further, we provide methods to obtain estimators for the probabilities of success for the various judgment order statistics under either perfect or imperfect rankings so that Neyman allocation can be implemented. Finally, we extend the application of RSS, both balanced and unbalanced, to ordered categorical variables with the goal of estimating the probabilities of all categories. We use ordinal logistic regression to aid in the ranking of the ordinal variable of interest. We also propose an optimal allocation scheme and methods for implementing it under either perfect or imperfect rankings. The results indicate that the use of ordinal logistic regression in ranking leads to substantial gains in precision for estimation of population proportions.

Estimation of the Variance for Logistic Distribution Under Ranked Set Sampling and Simple Random Sampling

Estimation of the Variance for Logistic Distribution Under Ranked Set Sampling and Simple Random Sampling Book
Author : S.A. Al-Subh,W. A. Abu-Dayyeh
Publisher : Unknown
Release : 2012
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Estimation of the Variance for Logistic Distribution Under Ranked Set Sampling and Simple Random Sampling book written by S.A. Al-Subh,W. A. Abu-Dayyeh, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Bayesian Nonparametric Models for Ranked Set Sampling

Bayesian Nonparametric Models for Ranked Set Sampling Book
Author : Nader M. Gemayel
Publisher : Unknown
Release : 2010
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Abstract: Ranked Set Sampling (RSS) is a data collection technique that combines measurement with judgment ranking for statistical inference. After a brief review of the basics of RSS, this dissertation lays out a formal and natural Bayesian framework for RSS that is analogous to its frequentist justification, and that does not require the assumption of perfect ranking or use of any imperfect ranking models. Prior beliefs about the judgment order statistic distributions and their interdependence are embodied by a nonparametric prior distribution. Posterior inference is carried out by means of Markov Chain Monte Carlo (MCMC) techniques, and yields estimators of the judgment order statistic distributions (and of functionals of those distributions). Because of non-conjugacy, different MCMC algorithms are used for continuous and discrete data. Judgment post-stratification is introduced to answer questions about handling information from multiple rankers, the quality of judgment ranking, and the role of set size. Finally, a more specific model is proposed for RSS with judgment ranking via a concomitant variable.

Use of Ranking Information from Unmeasured Units in Ranked Set and Judgement Post Stratified Samples

Use of Ranking Information from Unmeasured Units in Ranked Set and Judgement Post Stratified Samples Book
Author : Anthony James Sgambellone
Publisher : Unknown
Release : 2013
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Abstract: Judgement post-stratified (JPS) and ranked set sampling (RSS) are known to produce samples that are often more efficient per measurement than simple random sampling due to the use of auxiliary ranking information of unmeasured units. We believe common estimation methods for JPS and RSS do not use all potential information that unmeasured observations may contribute. We introduce new estimators that incorporate this information on the stochastic relationship between ranks of measured units and information from unmeasured units. For example, our estimator uses the knowledge that a measurement from a unit in the third judgement class is expected to be larger than measurements from units in the second and first judgement classes.

Ranked Set Sampling

Ranked Set Sampling Book
Author : Ramzi William Nahhas
Publisher : Unknown
Release : 1999
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Ranked Set Sampling book written by Ramzi William Nahhas, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

The Theory and Some Applications of Ranked Set Sampling

The Theory and Some Applications of Ranked Set Sampling Book
Author : Tommy Ray Dell
Publisher : Unknown
Release : 1969
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download The Theory and Some Applications of Ranked Set Sampling book written by Tommy Ray Dell, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Extending Ranked Set Sampling to Survey Methodology

Extending Ranked Set Sampling to Survey Methodology Book
Author : Christopher J. Sroka
Publisher : Unknown
Release : 2008
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Abstract: Ranked set sampling (RSS) is a method of data collection that makes use of the sampler's judgment of relative sizes of potential sample units. In RSS, the observations quantified by the researcher generally will be more representative of the range of values in the population than those obtained from simple random sampling (SRS). RSS has been shown to result in more precise estimators than SRS. Although there is a growing body of research on RSS, the area is unfamiliar to most sampling statisticians. In this dissertation, we demonstrate how RSS can be utilized in survey sampling settings. We begin by exploring the feasibility of incorporating RSS into a stratified sampling design. We call this technique stratified ranked set sampling (SRSS). In addition to its value as a sampling device, stratified sampling forms the theoretical basis of more complex sampling designs. By exploring RSS in stratified sampling first, we are laying the foundations for further research on how RSS can be incorporated into methodologies commonly used by survey samplers. We develop the theory of how to construct confidence intervals for the estimator of the mean under SRSS. Our simulations show that in most circumstances these confidence intervals are shorter than those under stratified SRS. We describe methods to search for the best way to allocate observations to the strata and ranks under SRSS. The number of possible allocations is extremely large, even for nominally small problems. This precludes an exhaustive search, so we turn our attention to methods that search subsets of the allocation space. Simulated annealing is an attractive method because it is easy to program and computationally efficient. When the optimal allocation assigns zero observations to a particular rank, the resultant estimator may be horribly biased. We investigate two methods to deal with this problem. We digress from SRSS at the end of this dissertation to discuss ratio estimation under RSS. Ratio estimation is another method that is commonly used in survey sampling. We provide some insight into the best selection of variables to use in RSS ratio estimation if one wants to minimize the MSE of the estimator.