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Handbook of Bayesian Survey Methods
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Handbook of Bayesian Survey Methods (Hardback)

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Bayesian methodology is well-developed, and there are successful applications in many areas of research. However, the use of such methodology in survey sampling and making inferences about finite population quantities has been limited. Handbook of Bayesian Survey Methods provides a comprehensive treatment of Bayesian survey methods, presenting the theory, methodology, and interesting, real-world applications related to this rapidly-evolving field of research. The author team draws on their extensive experience both as professors and government researchers to demonstrate the applicability of Bayesian ideas to survey sampling, while also discussing the latest research and computational developments. The book begins with an introduction to Bayesian perspectives on survey design and an overview of classic Bayesian literature of survey methods. Next, stratified sampling is outlined with coverage of optimal sample size allocation and two-phase sampling with stratification. Subsequent chapters treat issues related to weighting; provide an overview on cluster sampling; and delve into nonsampling errors. The major topic of small area estimation is treated in a way that both discusses the current literature on hierarchical Bayes methods and then explores recent developments related to accounting for nonresponse, selection effects, and more complex design and models. The authors conclude with an extensive chapter on cutting-edge topics that shed light on the direction of the field, including as sequential sampling; order restrictions; longitudinal surveys; Bayesian neural networks; link-tracing sampling designs; and trimmed weights. Each chapter follows the same easy-to-follow format. Following an introduction, a historical background on the topic is presented, followed by a description of related theory, applications, and key formulae. A summary provides a brief overview of main concepts, and a reference section outlines resources for further study of the topic. Where appropriate, real-world examples and applications are discussed and an extensive literature review directs readers to the classic literature on the topic and resources for further understanding of advanced concepts.

Reference & ResearchResearch & information: generalResearch methods: generalScience & MathematicsMathematicsProbability & statistics Publisher: John Wiley and Sons Ltd Publication Date: 04/02/2021 ISBN-13: 9781118074961  Details: Type: Hardback Format: Books
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