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Author: Risto Lehtonen
Publisher: John Wiley & Sons
ISBN: 0470091630
Category : Mathematics
Languages : en
Pages : 360
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Book Description
Large surveys are becoming increasingly available for public use, and researchers are often faced with the need to analyse complex survey data to address key scientific issues. For proper analysis it is also important to be aware of the different aspects of the design of complex surveys. Practical Methods for Design and Analysis of Complex Surveys features intermediate and advanced statistical techniques for use in designing and analysing complex surveys. This extensively updated edition features much new material, and detailed practical exercises with links to a Web site, helping instructors and enabling use for distance learning. * Provides a comprehensive introduction to sampling and estimation in descriptive surveys, including design effect statistic and use of auxiliary data. * Includes detailed coverage of complex survey analysis, including design-based ANOVA and logistic regression with GEE estimation. * Contains much new material, including handling of non-sampling errors, and model-assisted estimation for domains. * Features detailed real-li fe case studies, such as multilevel modeling in a multinational educational survey. * Supported by a Web site containing software codes, real data sets, computerized exercises with solutions, and online training materials. Practical Methods for Design and Analysis of Complex Surveys provides a useful practical resource for researchers and practitioners working in the planning, implementation or analysis of complex surveys and opinion polls, including business, educational, health, social, and socio-economic surveys and official statistics. In addition, the book is well suited for use on intermediate and advanced courses in survey sampling.
Author: Risto Lehtonen
Publisher: John Wiley & Sons
ISBN: 0470091630
Category : Mathematics
Languages : en
Pages : 360
Get Book Here
Book Description
Large surveys are becoming increasingly available for public use, and researchers are often faced with the need to analyse complex survey data to address key scientific issues. For proper analysis it is also important to be aware of the different aspects of the design of complex surveys. Practical Methods for Design and Analysis of Complex Surveys features intermediate and advanced statistical techniques for use in designing and analysing complex surveys. This extensively updated edition features much new material, and detailed practical exercises with links to a Web site, helping instructors and enabling use for distance learning. * Provides a comprehensive introduction to sampling and estimation in descriptive surveys, including design effect statistic and use of auxiliary data. * Includes detailed coverage of complex survey analysis, including design-based ANOVA and logistic regression with GEE estimation. * Contains much new material, including handling of non-sampling errors, and model-assisted estimation for domains. * Features detailed real-li fe case studies, such as multilevel modeling in a multinational educational survey. * Supported by a Web site containing software codes, real data sets, computerized exercises with solutions, and online training materials. Practical Methods for Design and Analysis of Complex Surveys provides a useful practical resource for researchers and practitioners working in the planning, implementation or analysis of complex surveys and opinion polls, including business, educational, health, social, and socio-economic surveys and official statistics. In addition, the book is well suited for use on intermediate and advanced courses in survey sampling.
Author: Thomas Lumley
Publisher: John Wiley & Sons
ISBN: 111821093X
Category : Mathematics
Languages : en
Pages : 329
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Book Description
A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.
Author: Taylor H. Lewis
Publisher: CRC Press
ISBN: 1498776809
Category : Mathematics
Languages : en
Pages : 341
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Book Description
Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures. The book offers comprehensive coverage of the most essential topics, including: Drawing random samples Descriptive statistics for continuous and categorical variables Fitting and interpreting linear and logistic regression models Survival analysis Domain estimation Replication variance estimation methods Weight adjustment and imputation methods for handling missing data The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author’s website: http://mason.gmu.edu/~tlewis18/. While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation. Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.
Author: Richard Valliant
Publisher: Springer Science & Business Media
ISBN: 1461464498
Category : Social Science
Languages : en
Pages : 678
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Book Description
Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.
Author: Steven G. Heeringa
Publisher: CRC Press
ISBN: 1498761615
Category : Mathematics
Languages : en
Pages : 591
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Book Description
Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.
Author: Sharon L. Lohr
Publisher: CRC Press
ISBN: 1000022080
Category : Mathematics
Languages : en
Pages : 611
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Book Description
This edition is a reprint of the second edition published by Cengage Learning, Inc. Reprinted with permission. What is the unemployment rate? How many adults have high blood pressure? What is the total area of land planted with soybeans? Sampling: Design and Analysis tells you how to design and analyze surveys to answer these and other questions. This authoritative text, used as a standard reference by numerous survey organizations, teaches sampling using real data sets from social sciences, public opinion research, medicine, public health, economics, agriculture, ecology, and other fields. The book is accessible to students from a wide range of statistical backgrounds. By appropriate choice of sections, it can be used for a graduate class for statistics students or for a class with students from business, sociology, psychology, or biology. Readers should be familiar with concepts from an introductory statistics class including linear regression; optional sections contain the statistical theory, for readers who have studied mathematical statistics. Distinctive features include: More than 450 exercises. In each chapter, Introductory Exercises develop skills, Working with Data Exercises give practice with data from surveys, Working with Theory Exercises allow students to investigate statistical properties of estimators, and Projects and Activities Exercises integrate concepts. A solutions manual is available. An emphasis on survey design. Coverage of simple random, stratified, and cluster sampling; ratio estimation; constructing survey weights; jackknife and bootstrap; nonresponse; chi-squared tests and regression analysis. Graphing data from surveys. Computer code using SAS® software. Online supplements containing data sets, computer programs, and additional material. Sharon Lohr, the author of Measuring Crime: Behind the Statistics, has published widely about survey sampling and statistical methods for education, public policy, law, and crime. She has been recognized as Fellow of the American Statistical Association, elected member of the International Statistical Institute, and recipient of the Gertrude M. Cox Statistics Award and the Deming Lecturer Award. Formerly Dean’s Distinguished Professor of Statistics at Arizona State University and a Vice President at Westat, she is now a freelance statistical consultant and writer. Visit her website at www.sharonlohr.com.
Author: C. J. Skinner
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 334
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Book Description
This study discusses appropriate principles and methods for the analysis of surveys, such as stratified multi-stage sampling, as well as the complex structure of the populations upon which these designs are based. It features essays on current research written by international experts.
Author: R. L. Chambers
Publisher: John Wiley & Sons
ISBN: 0470864397
Category : Mathematics
Languages : en
Pages : 398
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Book Description
This book is concerned with statistical methods for the analysis of data collected from a survey. A survey could consist of data collected from a questionnaire or from measurements, such as those taken as part of a quality control process. Concerned with the statistical methods for the analysis of sample survey data, this book will update and extend the successful book edited by Skinner, Holt and Smith on 'Analysis of Complex Surveys'. The focus will be on methodological issues, which arise when applying statistical methods to sample survey data and will discuss in detail the impact of complex sampling schemes. Further issues, such as how to deal with missing data and measurement of error will also be critically discussed. There have significant improvements in statistical software which implement complex sampling schemes (eg SUDAAN, STATA, WESVAR, PC CARP ) in the last decade and there is greater need for practical advice for those analysing survey data. To ensure a broad audience, the statistical theory will be made accessible through the use of practical examples. This book will be accessible to a broad audience of statisticians but will primarily be of interest to practitioners analysing survey data. Increased awareness by social scientists of the variety of powerful statistical methods will make this book a useful reference.
Author: Raghunath Arnab
Publisher: Academic Press
ISBN: 0128118970
Category : Mathematics
Languages : en
Pages : 932
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Book Description
Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling. The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students. - Covers a wide spectrum of topics on survey sampling and statistics - Serves as an ideal text for graduate students and researchers in survey sampling theory and applications - Contains material on recent developments in survey sampling not covered in other books - Illustrates theories using numerical examples and exercises
Author: Paul J. Lavrakas
Publisher: John Wiley & Sons
ISBN: 1119083753
Category : Social Science
Languages : en
Pages : 548
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Book Description
A thorough and comprehensive guide to the theoretical, practical, and methodological approaches used in survey experiments across disciplines such as political science, health sciences, sociology, economics, psychology, and marketing This book explores and explains the broad range of experimental designs embedded in surveys that use both probability and non-probability samples. It approaches the usage of survey-based experiments with a Total Survey Error (TSE) perspective, which provides insight on the strengths and weaknesses of the techniques used. Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment addresses experiments on within-unit coverage, reducing nonresponse, question and questionnaire design, minimizing interview measurement bias, using adaptive design, trend data, vignettes, the analysis of data from survey experiments, and other topics, across social, behavioral, and marketing science domains. Each chapter begins with a description of the experimental method or application and its importance, followed by reference to relevant literature. At least one detailed original experimental case study then follows to illustrate the experimental method’s deployment, implementation, and analysis from a TSE perspective. The chapters conclude with theoretical and practical implications on the usage of the experimental method addressed. In summary, this book: Fills a gap in the current literature by successfully combining the subjects of survey methodology and experimental methodology in an effort to maximize both internal validity and external validity Offers a wide range of types of experimentation in survey research with in-depth attention to their various methodologies and applications Is edited by internationally recognized experts in the field of survey research/methodology and in the usage of survey-based experimentation —featuring contributions from across a variety of disciplines in the social and behavioral sciences Presents advances in the field of survey experiments, as well as relevant references in each chapter for further study Includes more than 20 types of original experiments carried out within probability sample surveys Addresses myriad practical and operational aspects for designing, implementing, and analyzing survey-based experiments by using a Total Survey Error perspective to address the strengths and weaknesses of each experimental technique and method Experimental Methods in Survey Research: Techniques that Combine Random Sampling with Random Assignment is an ideal reference for survey researchers and practitioners in areas such political science, health sciences, sociology, economics, psychology, public policy, data collection, data science, and marketing. It is also a very useful textbook for graduate-level courses on survey experiments and survey methodology.
