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Author : Bart Buelens
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (929 download)
Download or read book Predictive Inference for Non-probability Samples written by Bart Buelens and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Seymour Geisser
Publisher : Routledge
ISBN 13 : 1351422294
Total Pages : 280 pages
Book Rating : 4.3/5 (514 download)
Download or read book Predictive Inference written by Seymour Geisser and published by Routledge. This book was released on 2017-11-22 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author's research has been directed towards inference involving observables rather than parameters. In this book, he brings together his views on predictive or observable inference and its advantages over parametric inference. While the book discusses a variety of approaches to prediction including those based on parametric, nonparametric, and nonstochastic statistical models, it is devoted mainly to predictive applications of the Bayesian approach. It not only substitutes predictive analyses for parametric analyses, but it also presents predictive analyses that have no real parametric analogues. It demonstrates that predictive inference can be a critical component of even strict parametric inference when dealing with interim analyses. This approach to predictive inference will be of interest to statisticians, psychologists, econometricians, and sociologists.
Author : Lawrence N. Dworsky
Publisher : John Wiley & Sons
ISBN 13 : 1119518105
Total Pages : 352 pages
Book Rating : 4.1/5 (195 download)
Download or read book Probably Not written by Lawrence N. Dworsky and published by John Wiley & Sons. This book was released on 2019-09-04 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A revised edition that explores random numbers, probability, and statistical inference at an introductory mathematical level Written in an engaging and entertaining manner, the revised and updated second edition of Probably Not continues to offer an informative guide to probability and prediction. The expanded second edition contains problem and solution sets. In addition, the book’s illustrative examples reveal how we are living in a statistical world, what we can expect, what we really know based upon the information at hand and explains when we only think we know something. The author introduces the principles of probability and explains probability distribution functions. The book covers combined and conditional probabilities and contains a new section on Bayes Theorem and Bayesian Statistics, which features some simple examples including the Presecutor’s Paradox, and Bayesian vs. Frequentist thinking about statistics. New to this edition is a chapter on Benford’s Law that explores measuring the compliance and financial fraud detection using Benford’s Law. This book: Contains relevant mathematics and examples that demonstrate how to use the concepts presented Features a new chapter on Benford’s Law that explains why we find Benford’s law upheld in so many, but not all, natural situations Presents updated Life insurance tables Contains updates on the Gantt Chart example that further develops the discussion of random events Offers a companion site featuring solutions to the problem sets within the book Written for mathematics and statistics students and professionals, the updated edition of Probably Not: Future Prediction Using Probability and Statistical Inference, Second Edition combines the mathematics of probability with real-world examples. LAWRENCE N. DWORSKY, PhD, is a retired Vice President of the Technical Staff and Director of Motorola’s Components Research Laboratory in Schaumburg, Illinois, USA. He is the author of Introduction to Numerical Electrostatics Using MATLAB from Wiley.
Author : Richard Valliant
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 546 pages
Book Rating : 4.3/5 (91 download)
Download or read book Finite Population Sampling and Inference written by Richard Valliant and published by Wiley-Interscience. This book was released on 2000-09-08 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Author : Seymour Geisser
Publisher :
ISBN 13 : 9781489944672
Total Pages : 264 pages
Book Rating : 4.9/5 (446 download)
Download or read book Predictive Inference written by Seymour Geisser and published by . This book was released on 1993 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Paul J. Lavrakas
Publisher : SAGE Publications
ISBN 13 : 150631788X
Total Pages : 1073 pages
Book Rating : 4.5/5 (63 download)
Download or read book Encyclopedia of Survey Research Methods written by Paul J. Lavrakas and published by SAGE Publications. This book was released on 2008-09-12 with total page 1073 pages. Available in PDF, EPUB and Kindle. Book excerpt: To the uninformed, surveys appear to be an easy type of research to design and conduct, but when students and professionals delve deeper, they encounter the vast complexities that the range and practice of survey methods present. To complicate matters, technology has rapidly affected the way surveys can be conducted; today, surveys are conducted via cell phone, the Internet, email, interactive voice response, and other technology-based modes. Thus, students, researchers, and professionals need both a comprehensive understanding of these complexities and a revised set of tools to meet the challenges. In conjunction with top survey researchers around the world and with Nielsen Media Research serving as the corporate sponsor, the Encyclopedia of Survey Research Methods presents state-of-the-art information and methodological examples from the field of survey research. Although there are other "how-to" guides and references texts on survey research, none is as comprehensive as this Encyclopedia, and none presents the material in such a focused and approachable manner. With more than 600 entries, this resource uses a Total Survey Error perspective that considers all aspects of possible survey error from a cost-benefit standpoint. Key Features Covers all major facets of survey research methodology, from selecting the sample design and the sampling frame, designing and pretesting the questionnaire, data collection, and data coding, to the thorny issues surrounding diminishing response rates, confidentiality, privacy, informed consent and other ethical issues, data weighting, and data analyses Presents a Reader′s Guide to organize entries around themes or specific topics and easily guide users to areas of interest Offers cross-referenced terms, a brief listing of Further Readings, and stable Web site URLs following most entries The Encyclopedia of Survey Research Methods is specifically written to appeal to beginning, intermediate, and advanced students, practitioners, researchers, consultants, and consumers of survey-based information.
Author : Carl-Erik Särndal
Publisher : John Wiley & Sons
ISBN 13 : 0470011343
Total Pages : 212 pages
Book Rating : 4.4/5 (7 download)
Download or read book Estimation in Surveys with Nonresponse written by Carl-Erik Särndal and published by John Wiley & Sons. This book was released on 2005-08-05 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Around the world a multitude of surveys are conducted every day, on a variety of subjects, and consequently surveys have become an accepted part of modern life. However, in recent years survey estimates have been increasingly affected by rising trends in nonresponse, with loss of accuracy as an undesirable result. Whilst it is possible to reduce nonresponse to some degree, it cannot be completely eliminated. Estimation techniques that account systematically for nonresponse and at the same time succeed in delivering acceptable accuracy are much needed. Estimation in Surveys with Nonresponse provides an overview of these techniques, presenting the view of nonresponse as a normal (albeit undesirable) feature of a sample survey, one whose potentially harmful effects are to be minimised. Builds in the nonresponse feature of survey data collection as an integral part of the theory, both for point estimation and for variance estimation. Promotes weighting through calibration as a new and powerful technique for surveys with nonresponse. Highlights the analysis of nonresponse bias in estimates and methods to minimize this bias. Includes computational tools to help identify the best variables for calibration. Discusses the use of imputation as a complement to weighting by calibration. Contains guidelines for dealing with frame imperfections and coverage errors. Features worked examples throughout the text, using real data. The accessible style of Estimation in Surveys with Nonresponse will make this an invaluable tool for survey methodologists in national statistics agencies and private survey agencies. Researchers, teachers, and students of statistics, social sciences and economics will benefit from the clear presentation and numerous examples.
Author : Claes-Magnus Cassel
Publisher :
ISBN 13 :
Total Pages : 216 pages
Book Rating : 4.:/5 (49 download)
Download or read book Foundations of Inference in Survey Sampling written by Claes-Magnus Cassel and published by . This book was released on 1977-08-31 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Parimal Mukhopadhyay
Publisher : New Age International
ISBN 13 : 9788122407549
Total Pages : 266 pages
Book Rating : 4.4/5 (75 download)
Download or read book Inferential Problems in Survey Sampling written by Parimal Mukhopadhyay and published by New Age International. This book was released on 1996 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Book Provides A Comprehensive Account Of Survey Sampling Theory In Fixed Population Approach And Model Based Approach. After Making A Critical Review Of Different Results In Fixed Population Set Up It Shows How Super Population Models Can Be Exploited To Produce Optimal And Robust Sampling Strategies, Specially In Large Scale Sample Surveys. The Central Theme Of The Book Is The Use Of Super Population Models In Making Inference From Sample Surveys. The Book Also Gives Suitable Emphasis On Different Practical Aspects, Like Choice Of Sampling Designs, Variance Estimation, Different Replication And Resampling Procedures.The Author Has Taken Care To Presuppose Nothing More On The Part Of The Reader Than A First Course In Statistical Inference, Sampling Theory And Regression Analysis. He Has Systematically Arranged The Main Results, Supplied Short Proofs, Examples, Explanatory Notes And Remarks And Indicated Research Areas. The Book Will Be Very Useful To Researchers. The Survey Practitioners Will Also Find Some Part Of The Book Very Helpful.
Author : Frank Coolen
Publisher : Wiley-Blackwell
ISBN 13 : 9780470723340
Total Pages : 256 pages
Book Rating : 4.7/5 (233 download)
Download or read book Nonparametric Predictive Inference written by Frank Coolen and published by Wiley-Blackwell. This book was released on 2012-06-15 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will be the first on NPI and will provide an introduction to and overview of, the approach′s current state of the art. It will be a self-contained treatment of the subject, introducing it to readers, and leading them on to a more advanced and specialist understanding. The Author compares and contrasts NPI theory with classical statistical theory, pointing out the ways in which NPI can enhance current research in areas ranging from operations research to engineering and artificial intelligence. After the initial introductory chapter, the book provides a series of chapters outlining the use of NPI in specific settings, e.g. for real-valued random quantities or for multinomial data. This will be followed by chapters detailing further applications in statistics, providing examples such as NPI for statistical quality and process control, reliability and operations research, with a variety of examples such as maintenance and replacement problems, queuing situations and risk reliability inferences. The foundations and ideas behind NPI will be presented along with an examination and comparison of more traditional approaches of classical and Bayesian statistics, providing further insights into the advantages of NPI. Future directions and the accommodation of multivariate data will also be discussed.
Author : Changbao Wu
Publisher : Springer Nature
ISBN 13 : 3030442462
Total Pages : 371 pages
Book Rating : 4.0/5 (34 download)
Download or read book Sampling Theory and Practice written by Changbao Wu and published by Springer Nature. This book was released on 2020-05-15 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Lawrence N. Dworsky
Publisher : John Wiley & Sons
ISBN 13 : 111951813X
Total Pages : 352 pages
Book Rating : 4.1/5 (195 download)
Download or read book Probably Not written by Lawrence N. Dworsky and published by John Wiley & Sons. This book was released on 2019-07-26 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A revised edition that explores random numbers, probability, and statistical inference at an introductory mathematical level Written in an engaging and entertaining manner, the revised and updated second edition of Probably Not continues to offer an informative guide to probability and prediction. The expanded second edition contains problem and solution sets. In addition, the book’s illustrative examples reveal how we are living in a statistical world, what we can expect, what we really know based upon the information at hand and explains when we only think we know something. The author introduces the principles of probability and explains probability distribution functions. The book covers combined and conditional probabilities and contains a new section on Bayes Theorem and Bayesian Statistics, which features some simple examples including the Presecutor’s Paradox, and Bayesian vs. Frequentist thinking about statistics. New to this edition is a chapter on Benford’s Law that explores measuring the compliance and financial fraud detection using Benford’s Law. This book: Contains relevant mathematics and examples that demonstrate how to use the concepts presented Features a new chapter on Benford’s Law that explains why we find Benford’s law upheld in so many, but not all, natural situations Presents updated Life insurance tables Contains updates on the Gantt Chart example that further develops the discussion of random events Offers a companion site featuring solutions to the problem sets within the book Written for mathematics and statistics students and professionals, the updated edition of Probably Not: Future Prediction Using Probability and Statistical Inference, Second Edition combines the mathematics of probability with real-world examples. LAWRENCE N. DWORSKY, PhD, is a retired Vice President of the Technical Staff and Director of Motorola’s Components Research Laboratory in Schaumburg, Illinois, USA. He is the author of Introduction to Numerical Electrostatics Using MATLAB from Wiley.
Author : Seymour Geisser
Publisher : John Wiley & Sons
ISBN 13 : 0471743127
Total Pages : 218 pages
Book Rating : 4.4/5 (717 download)
Download or read book Modes of Parametric Statistical Inference written by Seymour Geisser and published by John Wiley & Sons. This book was released on 2006-01-27 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fascinating investigation into the foundations of statistical inference This publication examines the distinct philosophical foundations of different statistical modes of parametric inference. Unlike many other texts that focus on methodology and applications, this book focuses on a rather unique combination of theoretical and foundational aspects that underlie the field of statistical inference. Readers gain a deeper understanding of the evolution and underlying logic of each mode as well as each mode's strengths and weaknesses. The book begins with fascinating highlights from the history of statistical inference. Readers are given historical examples of statistical reasoning used to address practical problems that arose throughout the centuries. Next, the book goes on to scrutinize four major modes of statistical inference: * Frequentist * Likelihood * Fiducial * Bayesian The author provides readers with specific examples and counterexamples of situations and datasets where the modes yield both similar and dissimilar results, including a violation of the likelihood principle in which Bayesian and likelihood methods differ from frequentist methods. Each example is followed by a detailed discussion of why the results may have varied from one mode to another, helping the reader to gain a greater understanding of each mode and how it works. Moreover, the author provides considerable mathematical detail on certain points to highlight key aspects of theoretical development. The author's writing style and use of examples make the text clear and engaging. This book is fundamental reading for graduate-level students in statistics as well as anyone with an interest in the foundations of statistics and the principles underlying statistical inference, including students in mathematics and the philosophy of science. Readers with a background in theoretical statistics will find the text both accessible and absorbing.
Author : Andreas Quatember
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (112 download)
Download or read book Inferences Based on Probability Sampling Or Nonprobability Sampling: Are They Nothing But a Question of Models?. written by Andreas Quatember and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The inferential quality of an available data set, be it from a probability sample or a nonprobability sample, is discussed under the standard of the representativeness of a sample with regard to interesting characteristics, which implicitly includes the consideration of the total survey error. The paper focuses on the assumptions that are made when calculating an estimator of a certain population characteristic using a specific sampling method, and on the model-based repair methods, which can be applied in the case of deviations from these assumptions. The different implicit assumptions regarding operationalization, frame, selection method, nonresponse, measurement, and data processing are considered exemplarily for the Horvitz-Thompson estimator of a population total. In particular, the remarkable effect of a deviation from the assumption concerning the selection method is discussed. It is shown that there are far more unverifiable, disputable models addressing the different impli
Author : Denis Bosq
Publisher : John Wiley & Sons
ISBN 13 : 9780470724026
Total Pages : 336 pages
Book Rating : 4.7/5 (24 download)
Download or read book Inference and Prediction in Large Dimensions written by Denis Bosq and published by John Wiley & Sons. This book was released on 2008-03-11 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a predominantly theoretical coverage of statistical prediction, with some potential applications discussed, when data and/ or parameters belong to a large or infinite dimensional space. It develops the theory of statistical prediction, non-parametric estimation by adaptive projection – with applications to tests of fit and prediction, and theory of linear processes in function spaces with applications to prediction of continuous time processes. This work is in the Wiley-Dunod Series co-published between Dunod (www.dunod.com) and John Wiley and Sons, Ltd.
Author : Christof Wolf
Publisher : SAGE
ISBN 13 : 1473959047
Total Pages : 1065 pages
Book Rating : 4.4/5 (739 download)
Download or read book The SAGE Handbook of Survey Methodology written by Christof Wolf and published by SAGE. This book was released on 2016-07-11 with total page 1065 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survey Methodology is becoming a more structured field of research, deserving of more and more academic attention. The SAGE Handbook of Survey Methodology explores both the increasingly scientific endeavour of surveys and their growing complexity, as different data collection modes and information sources are combined. The handbook takes a global approach, with a team of international experts looking at local and national specificities, as well as problems of cross-national, comparative survey research. The chapters are organized into seven major sections, each of which represents a stage in the survey life-cycle: Surveys and Societies Planning a Survey Measurement Sampling Data Collection Preparing Data for Use Assessing and Improving Data Quality The SAGE Handbook of Survey Methodology is a landmark and essential tool for any scholar within the social sciences.
Author : Jim Albert
Publisher : CRC Press
ISBN 13 : 1351030124
Total Pages : 511 pages
Book Rating : 4.3/5 (51 download)
Download or read book Probability and Bayesian Modeling written by Jim Albert and published by CRC Press. This book was released on 2019-12-06 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.
