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Design and Inference in Finite Population Sampling

Design and Inference in Finite Population Sampling
Author: A. S. Hedayat
Publisher: Wiley-Interscience
Total Pages: 0
Release: 1991-09-03
Genre: Science
ISBN: 9780471880738

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Covers a new but essential development in the field of population sampling, namely inference in finite sampling. Offers some important topics not found in other texts on sampling such as the superpopulation approach and randomized response, nonresponse and resampling techniques.


Finite Population Sampling and Inference

Finite Population Sampling and Inference
Author: Richard Valliant
Publisher: Wiley-Interscience
Total Pages: 546
Release: 2000-09-08
Genre: Mathematics
ISBN:

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Complete coverage of the prediction approach to survey sampling in a single resource Prediction theory has been extremely influential in survey sampling for nearly three decades, yet research findings on this model-based approach are scattered in disparate areas of the statistical literature. Finite Population Sampling and Inference: A Prediction Approach presents for the first time a unified treatment of sample design and estimation for finite populations from a prediction point of view, providing readers with access to a wealth of theoretical results, including many new results and, a variety of practical applications. Geared to theoretical statisticians and practitioners alike, the book discusses all topics from the ground up and clearly explains the relation of the prediction approach to the traditional design-based randomization approach. Key features include: * Special emphasis on linking survey sampling to mainstream statistics through extensive use of general linear models * A liberal use of simulation studies, numerical examples, and exercises illustrating theoretical results * Numerous statistical graphics showing simulation results and properties of estimates * A library of S-Plus computer functions plus six real populations, available via ftp * Over 260 references to finite population sampling, linear models, and other relevant literature


Sampling and Estimation from Finite Populations

Sampling and Estimation from Finite Populations
Author: Yves Tille
Publisher: John Wiley & Sons
Total Pages: 447
Release: 2020-03-30
Genre: Mathematics
ISBN: 0470682051

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A much-needed reference on survey sampling and its applications that presents the latest advances in the field Seeking to show that sampling theory is a living discipline with a very broad scope, this book examines the modern development of the theory of survey sampling and the foundations of survey sampling. It offers readers a critical approach to the subject and discusses putting theory into practice. It also explores the treatment of non-sampling errors featuring a range of topics from the problems of coverage to the treatment of non-response. In addition, the book includes real examples, applications, and a large set of exercises with solutions. Sampling and Estimation from Finite Populations begins with a look at the history of survey sampling. It then offers chapters on: population, sample, and estimation; simple and systematic designs; stratification; sampling with unequal probabilities; balanced sampling; cluster and two-stage sampling; and other topics on sampling, such as spatial sampling, coordination in repeated surveys, and multiple survey frames. The book also includes sections on: post-stratification and calibration on marginal totals; calibration estimation; estimation of complex parameters; variance estimation by linearization; and much more. Provides an up-to-date review of the theory of sampling Discusses the foundation of inference in survey sampling, in particular, the model-based and design-based frameworks Reviews the problems of application of the theory into practice Also deals with the treatment of non sampling errors Sampling and Estimation from Finite Populations is an excellent book for methodologists and researchers in survey agencies and advanced undergraduate and graduate students in social science, statistics, and survey courses.


Foundations of Inference in Survey Sampling

Foundations of Inference in Survey Sampling
Author: Claes-Magnus Cassel
Publisher:
Total Pages: 216
Release: 1977-08-31
Genre: Mathematics
ISBN:

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Basic model of sampling from a population with identifiable units; Inference under the fixed population model: the concepts of sufficiency and likelihood; inference under the fixed population model: criteria for judging estimators and strategies; Inference under superpopulation models: design-unbiased estimation; Inference under superpopulation models: prediction approach using tools of classical inference; Inference under superpopulation models: using tools of bayesian inference; Efficiency robust estimation of the finite population mean.


Adaptive Sampling Designs

Adaptive Sampling Designs
Author: George A.F. Seber
Publisher: Springer Science & Business Media
Total Pages: 78
Release: 2012-10-23
Genre: Mathematics
ISBN: 3642336566

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This book aims to provide an overview of some adaptive techniques used in estimating parameters for finite populations where the sampling at any stage depends on the sampling information obtained to date. The sample adapts to new information as it comes in. These methods are especially used for sparse and clustered populations. Written by two acknowledged experts in the field of adaptive sampling.


Model Assisted Survey Sampling

Model Assisted Survey Sampling
Author: Carl-Erik Särndal
Publisher: Springer Science & Business Media
Total Pages: 716
Release: 2003-10-31
Genre: Mathematics
ISBN: 9780387406206

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Now available in paperback, this book provides a comprehensive account of survey sampling theory and methodology suitable for students and researchers across a variety of disciplines. It shows how statistical modeling is a vital component of the sampling process and in the choice of estimation technique. The first textbook that systematically extends traditional sampling theory with the aid of a modern model assisted outlook. Covers classical topics as well as areas where significant new developments have taken place.


Sampling Theory and Practice

Sampling Theory and Practice
Author: Changbao Wu
Publisher: Springer Nature
Total Pages: 371
Release: 2020-05-15
Genre: Social Science
ISBN: 3030442462

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The three parts of this book on survey methodology combine an introduction to basic sampling theory, engaging presentation of topics that reflect current research trends, and informed discussion of the problems commonly encountered in survey practice. These related aspects of survey methodology rarely appear together under a single connected roof, making this book a unique combination of materials for teaching, research and practice in survey sampling. Basic knowledge of probability theory and statistical inference is assumed, but no prior exposure to survey sampling is required. The first part focuses on the design-based approach to finite population sampling. It contains a rigorous coverage of basic sampling designs, related estimation theory, model-based prediction approach, and model-assisted estimation methods. The second part stems from original research conducted by the authors as well as important methodological advances in the field during the past three decades. Topics include calibration weighting methods, regression analysis and survey weighted estimating equation (EE) theory, longitudinal surveys and generalized estimating equations (GEE) analysis, variance estimation and resampling techniques, empirical likelihood methods for complex surveys, handling missing data and non-response, and Bayesian inference for survey data. The third part provides guidance and tools on practical aspects of large-scale surveys, such as training and quality control, frame construction, choices of survey designs, strategies for reducing non-response, and weight calculation. These procedures are illustrated through real-world surveys. Several specialized topics are also discussed in detail, including household surveys, telephone and web surveys, natural resource inventory surveys, adaptive and network surveys, dual-frame and multiple frame surveys, and analysis of non-probability survey samples. This book is a self-contained introduction to survey sampling that provides a strong theoretical base with coverage of current research trends and pragmatic guidance and tools for conducting surveys.


Sample Surveys: Inference and Analysis

Sample Surveys: Inference and Analysis
Author:
Publisher: Morgan Kaufmann
Total Pages: 667
Release: 2009-09-02
Genre: Mathematics
ISBN: 0080963544

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Handbook of Statistics_29B contains the most comprehensive account of sample surveys theory and practice to date. It is a second volume on sample surveys, with the goal of updating and extending the sampling volume published as volume 6 of the Handbook of Statistics in 1988. The present handbook is divided into two volumes (29A and 29B), with a total of 41 chapters, covering current developments in almost every aspect of sample surveys, with references to important contributions and available software. It can serve as a self contained guide to researchers and practitioners, with appropriate balance between theory and real life applications. Each of the two volumes is divided into three parts, with each part preceded by an introduction, summarizing the main developments in the areas covered in that part. Volume 1 deals with methods of sample selection and data processing, with the later including editing and imputation, handling of outliers and measurement errors, and methods of disclosure control. The volume contains also a large variety of applications in specialized areas such as household and business surveys, marketing research, opinion polls and censuses. Volume 2 is concerned with inference, distinguishing between design-based and model-based methods and focusing on specific problems such as small area estimation, analysis of longitudinal data, categorical data analysis and inference on distribution functions. The volume contains also chapters dealing with case-control studies, asymptotic properties of estimators and decision theoretic aspects. Comprehensive account of recent developments in sample survey theory and practice Covers a wide variety of diverse applications Comprehensive bibliography


Evaluation and Development of Strategies for Sample Coordination and Statistical Inference in Finite Population Sampling

Evaluation and Development of Strategies for Sample Coordination and Statistical Inference in Finite Population Sampling
Author:
Publisher:
Total Pages:
Release:
Genre:
ISBN:

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This Ph. D. thesis concentrates on two important subjects in survey sampling theory. One is the problem of the foundation for statistical inference in finite population sampling, and the other is the problem of coordination of samples over time. The thesis is based on four articles. Three of them are already published and the last one is submitted for publication. First, we show that the model-based and design-based inferences can be reconciliated if we search for an optimal strategy rather than just an optimal estimator, a strategy being a pair composed of a sampling design and an estimator. If we accept the idea that balanced samples are randomly selected, e.g. by the cube method, then we show that, under the linear model, an optimal strategy consists of a balanced sampling design with inclusion probabilities that are proportional to the standard deviations of the errors of the model and the Horvitz-Thompson estimator. Moreover, if the heteroscedasticity of the model is "fully explainable" by the auxiliary variables, then the best linear unbiased estimator and the Horvitz-Thompson estimator are equal. We construct a single estimator for both the design and model variance. The inference can thus be valid under the sampling design and under the model. Finally, we show that this strategy is robust and efficient when the model is misspecified. Coordination of probabilistic samples is a challenging theoretical problem faced by statistical institutes. One of their aims is to maximize or minimize the overlap between several samples drawn successively in a population that changes over time. In order to do that, a dependence between the samples must be introduced. Several methods for coordinating stratified samples have already been developed. Using simulations, we compare their optimality and quality of coordination. We present new methods based on Permanent Random Numbers (PRNs) and microstrata which have the advantage of allowing us to choose between positive or negative.