Measurement Errors In Surveys
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Measurement Errors In Surveys
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Author : Paul P. Biemer
language : en
Publisher: John Wiley & Sons
Release Date : 2013-08-12
Measurement Errors In Surveys written by Paul P. Biemer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-12 with Mathematics categories.
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book will be an aid to survey statisticians and to research workers who must work with survey data." –Short Book Reviews, International Statistical Institute Measurement Errors in Surveys documents the current state of the field, reports new research findings, and promotes interdisciplinary exchanges in modeling, assessing, and reducing measurement errors in surveys. Providing a fundamental approach to measurement errors, the book features sections on the questionnaire, respondents and responses, interviewers and other means of data collection, the respondent-interviewer relationship, and the effects of measurement errors on estimation and data analysis.
Margins Of Error
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Author : Duane F. Alwin
language : en
Publisher: John Wiley & Sons
Release Date : 2007-07-09
Margins Of Error written by Duane F. Alwin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-09 with Mathematics categories.
Enhance the quality of survey results by recognizing and reducing measurement errors. Margins of Error: A Study of Reliability in Survey Measurement demonstrates how and hwy identifying the presence and extent of measurement errors in survey data is essential for improving the overall collection and analysis of the data. The author outlines the consequences of ignoring survey measurement errors and also discusses ways to detect and estimate the impact of these errors. This book also provides recommendations of improving the quality of survey data. Logically organized and clearly written, this book: Deconstructs the data gathering process into six main elements of the response process: question adequacy, comprehension, accessibility, retrieval, motivation, and communication Provides an exhaustive review of valuable reliability estimation techniques that can be applied to survey data Identifies the types of questions and interviewer practices that are essential to the collection of reliable data Addresses hypotheses regarding which survey questions, sources of information, and questionnaire formats produce the most reliable data In conjunction with research data gathered on nearly 500 survey measures and the application of an empirical approach grounded in classical measurement theory, this book discusses the sources of measurement error and provides the tools necessary for improving survey data collection methods. Margins of Error enables statisticians and researchers in the fields of public opinion and survey research to design studies that can detect, estimate, and reduce measurement errors that may have previously gone undetected. This book also serves as a supplemental textbook for both undergraduate and graduate survey methodology courses.
Survey Errors And Survey Costs
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Author : Robert M. Groves
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-21
Survey Errors And Survey Costs written by Robert M. Groves and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-21 with Mathematics categories.
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Survey Errors and Survey Costs is a well-written, well-presented, and highly readable text that should be on every error-conscious statistician’s bookshelf. Any courses that cover the theory and design of surveys should certainly have Survey Errors and Survey Costs on their reading lists." –Phil Edwards MEL, Aston University Science Park, UK Review in The Statistician, Vol. 40, No. 3, 1991 "This volume is an extremely valuable contribution to survey methodology. It has many virtues: First, it provides a framework in which survey errors can be segregated by sources. Second, Groves has skillfully synthesized existing knowledge, bringing together in an easily accessible form empirical knowledge from a variety of sources. Third, he has managed to integrate into a common framework the contributions of several disciplines. For example, the work of psychometricians and cognitive psychologists is made relevant to the research of econometricians as well as the field experience of sociologists. Finally, but not least, Groves has managed to present all this in a style that is accessible to a wide variety of readers ranging from survey specialists to policymakers." –Peter H. Rossi University of Massachusetts at Amherst Review in Journal of Official Statistics, January 1991
Total Survey Error In Practice
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Author : Paul P. Biemer
language : en
Publisher: John Wiley & Sons
Release Date : 2017-02-21
Total Survey Error In Practice written by Paul P. Biemer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-21 with Social Science categories.
Featuring a timely presentation of total survey error (TSE), this edited volume introduces valuable tools for understanding and improving survey data quality in the context of evolving large-scale data sets This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields continue to evolve, leading to larger and messier data sets. This perspective challenges survey organizations to find ways to collect and process data more efficiently without sacrificing quality. The volume consists of the most up-to-date research and reporting from over 70 contributors representing the best academics and researchers from a range of fields. The chapters are broken out into five main sections: The Concept of TSE and the TSE Paradigm, Implications for Survey Design, Data Collection and Data Processing Applications, Evaluation and Improvement, and Estimation and Analysis. Each chapter introduces and examines multiple error sources, such as sampling error, measurement error, and nonresponse error, which often offer the greatest risks to data quality, while also encouraging readers not to lose sight of the less commonly studied error sources, such as coverage error, processing error, and specification error. The book also notes the relationships between errors and the ways in which efforts to reduce one type can increase another, resulting in an estimate with larger total error. This book: • Features various error sources, and the complex relationships between them, in 25 high-quality chapters on the most up-to-date research in the field of TSE • Provides comprehensive reviews of the literature on error sources as well as data collection approaches and estimation methods to reduce their effects • Presents examples of recent international events that demonstrate the effects of data error, the importance of survey data quality, and the real-world issues that arise from these errors • Spans the four pillars of the total survey error paradigm (design, data collection, evaluation and analysis) to address key data quality issues in official statistics and survey research Total Survey Error in Practice is a reference for survey researchers and data scientists in research areas that include social science, public opinion, public policy, and business. It can also be used as a textbook or supplementary material for a graduate-level course in survey research methods.
Latent Class Analysis Of Survey Error
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Author : Paul P. Biemer
language : en
Publisher: John Wiley & Sons
Release Date : 2011-03-16
Latent Class Analysis Of Survey Error written by Paul P. Biemer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-16 with Mathematics categories.
Combining theoretical, methodological, and practical aspects, Latent Class Analysis of Survey Error successfully guides readers through the accurate interpretation of survey results for quality evaluation and improvement. This book is a comprehensive resource on the key statistical tools and techniques employed during the modeling and estimation of classification errors, featuring a special focus on both latent class analysis (LCA) techniques and models for categorical data from complex sample surveys. Drawing from his extensive experience in the field of survey methodology, the author examines early models for survey measurement error and identifies their similarities and differences as well as their strengths and weaknesses. Subsequent chapters treat topics related to modeling, estimating, and reducing errors in surveys, including: Measurement error modeling forcategorical data The Hui-Walter model and othermethods for two indicators The EM algorithm and its role in latentclass model parameter estimation Latent class models for three ormore indicators Techniques for interpretation of modelparameter estimates Advanced topics in LCA, including sparse data, boundary values, unidentifiability, and local maxima Special considerations for analyzing datafrom clustered and unequal probability samples with nonresponse The current state of LCA and MLCA (multilevel latent class analysis), and an insightful discussion on areas for further research Throughout the book, more than 100 real-world examples describe the presented methods in detail, and readers are guided through the use of lEM software to replicate the presented analyses. Appendices supply a primer on categorical data analysis, and a related Web site houses the lEM software. Extensively class-tested to ensure an accessible presentation, Latent Class Analysis of Survey Error is an excellent book for courses on measurement error and survey methodology at the graduate level. The book also serves as a valuable reference for researchers and practitioners working in business, government, and the social sciences who develop, implement, or evaluate surveys.
Measurement Error In Longitudinal Data
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Author : Alexandru Cernat
language : en
Publisher: Oxford University Press
Release Date : 2021-03-18
Measurement Error In Longitudinal Data written by Alexandru Cernat and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-18 with Science categories.
Longitudinal data is essential for understanding how the world around us changes. Most theories in the social sciences and elsewhere have a focus on change, be it of individuals, of countries, of organizations, or of systems, and this is reflected in the myriad of longitudinal data that are being collected using large panel surveys. This type of data collection has been made easier in the age of Big Data and with the rise of social media. Yet our measurements of the world are often imperfect, and longitudinal data is vulnerable to measurement errors which can lead to flawed and misleading conclusions. Measurement Error in Longitudinal Data tackles the important issue of how to investigate change in the context of imperfect data. It compiles the latest advances in estimating change in the presence of measurement error from several fields and covers the entire process, from the best ways of collecting longitudinal data, to statistical models to estimate change under uncertainty, to examples of researchers applying these methods in the real world. This book introduces the essential issues of longitudinal data collection, such as memory effects, panel conditioning (or mere measurement effects), the use of administrative data, and the collection of multi-mode longitudinal data. It also presents some of the most important models used in this area, including quasi-simplex models, latent growth models, latent Markov chains, and equivalence/DIF testing. Finally, the use of vignettes in the context of longitudinal data and estimation methods for multilevel models of change in the presence of measurement error are also discussed.
Total Survey Error In Practice
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Author : Paul P. Biemer
language : en
Publisher: John Wiley & Sons
Release Date : 2017-02-13
Total Survey Error In Practice written by Paul P. Biemer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-13 with Social Science categories.
Featuring a timely presentation of total survey error (TSE), this edited volume introduces valuable tools for understanding and improving survey data quality in the context of evolving large-scale data sets This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields continue to evolve, leading to larger and messier data sets. This perspective challenges survey organizations to find ways to collect and process data more efficiently without sacrificing quality. The volume consists of the most up-to-date research and reporting from over 70 contributors representing the best academics and researchers from a range of fields. The chapters are broken out into five main sections: The Concept of TSE and the TSE Paradigm, Implications for Survey Design, Data Collection and Data Processing Applications, Evaluation and Improvement, and Estimation and Analysis. Each chapter introduces and examines multiple error sources, such as sampling error, measurement error, and nonresponse error, which often offer the greatest risks to data quality, while also encouraging readers not to lose sight of the less commonly studied error sources, such as coverage error, processing error, and specification error. The book also notes the relationships between errors and the ways in which efforts to reduce one type can increase another, resulting in an estimate with larger total error. This book: • Features various error sources, and the complex relationships between them, in 25 high-quality chapters on the most up-to-date research in the field of TSE • Provides comprehensive reviews of the literature on error sources as well as data collection approaches and estimation methods to reduce their effects • Presents examples of recent international events that demonstrate the effects of data error, the importance of survey data quality, and the real-world issues that arise from these errors • Spans the four pillars of the total survey error paradigm (design, data collection, evaluation and analysis) to address key data quality issues in official statistics and survey research Total Survey Error in Practice is a reference for survey researchers and data scientists in research areas that include social science, public opinion, public policy, and business. It can also be used as a textbook or supplementary material for a graduate-level course in survey research methods.
The Total Survey Error Approach
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Author : Herbert F. Weisberg
language : en
Publisher: University of Chicago Press
Release Date : 2009-12-29
The Total Survey Error Approach written by Herbert F. Weisberg and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-29 with Social Science categories.
In 1939, George Gallup's American Institute of Public Opinion published a pamphlet optimistically titled The New Science of Public Opinion Measurement. At the time, though, survey research was in its infancy, and only now, six decades later, can public opinion measurement be appropriately called a science, based in part on the development of the total survey error approach. Herbert F. Weisberg's handbook presents a unified method for conducting good survey research centered on the various types of errors that can occur in surveys—from measurement and nonresponse error to coverage and sampling error. Each chapter is built on theoretical elements drawn from specific disciplines, such as social psychology and statistics, and follows through with detailed treatments of the specific types of error and their potential solutions. Throughout, Weisberg is attentive to survey constraints, including time and ethical considerations, as well as controversies within the field and the effects of new technology on the survey process—from Internet surveys to those completed by phone, by mail, and in person. Practitioners and students will find this comprehensive guide particularly useful now that survey research has assumed a primary place in both public and academic circles.
Survey Measurement And Process Quality
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Author : Lars Lyberg
language : en
Publisher: Wiley-Interscience
Release Date : 1997-02-24
Survey Measurement And Process Quality written by Lars Lyberg and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-02-24 with Mathematics categories.
An in-depth look at current issues, new research findings, and interdisciplinary exchange in survey methodology and processing Survey Measurement and Process Quality extends the marriage of traditional survey issues and continuous quality improvement further than any other contemporary volume. It documents the current state of the field, reports new research findings, and promotes interdisciplinary exchange in questionnaire design, data collection, data processing, quality assessment, and effects of errors on estimation and analysis. The book's five sections discuss a broad range of issues and topics in each of five major areas, including Questionnaire design—conceptualization, design of rating scales for effective measurement, self-administered questionnaires, and more Data collection—new technology, interviewer effects, interview mode, children as respondents Post-survey processing and operations—modeling of classification operations, coding based on such systems, editing, integrating processes Quality assessment and control—total quality management, developing current best methods, service quality, quality efforts across organizations Effects of misclassification on estimation, analysis, and interpretation—misclassification and other measurement errors, new variance estimators that account for measurement error, estimators of nonsampling error components in interview surveys Survey Measurement and Process Quality is an indispensable resource for survey practitioners and managers as well as an excellent supplemental text for undergraduate and graduate courses and special seminars.
Nonsampling Error In Social Surveys
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Author : David E. McNabb
language : en
Publisher: SAGE Publications
Release Date : 2013-07-30
Nonsampling Error In Social Surveys written by David E. McNabb and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-30 with Social Science categories.
A welcome and much-needed addition to the literature on survey data quality in social research, Nonsampling Error in Social Surveys, by David E. McNabb, examines the most common sources of nonsampling error: frame error; measurement error; response error, nonresponse error, and interviewer error. Offering the only comprehensive and non-technical treatment available, the book’s focus on controlling error shows readers how to eliminate the opportunity for error to occur, and features revealing examples of past and current efforts to control the incidence and effects of nonsampling error. Most importantly, it gives readers the tools they need to understand, identify, address, and prevent the most prevalent and difficult-to-control types of survey errors.