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Total survey error in practice

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Unknown Biemer, Paul P., John Wiley and Sons, Inc. (Hoboken, New Jersey, 2017) (eng) English 9781119041702 Wiley series in survey methodology Unknown SURVEYS; Includes index; 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.
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1 online resource (627 p.) Unknown Unknown
Summary / review / table of contents

Front Matter (Pages: i-xxvii)
Section 1 : The Concept of TSE and the TSE Paradigm
CHAPTER 1 The Roots and Evolution of the Total Survey Error Concept (Pages: 1-22)
CHAPTER 2 Total Twitter Error: Decomposing Public Opinion Measurement on Twitter from a Total Survey Error Perspective (Pages: 23-46)
CHAPTER 3 Big Data: A Survey Research Perspective (Pages: 47-69)
CHAPTER 4 The Role of Statistical Disclosure Limitation in Total Survey Error (Pages: 71-94)
Section 2 : Implications for Survey Design
CHAPTER 5 The Undercoverage–Nonresponse Tradeoff (Pages: 95-113)
CHAPTER 6 Mixing Modes: Tradeoffs Among Coverage, Nonresponse, and Measurement Error (Pages: 115-132)
CHAPTER 7 Mobile Web Surveys: A Total Survey Error Perspective (Pages: 133-154)
CHAPTER 8 The Effects of a Mid‐Data Collection Change in Financial Incentives on Total Survey Error in the National Survey of Family Growth: Results from a Randomized Experiment (Pages: 155-177)
CHAPTER 9 A Total Survey Error Perspective on Surveys in Multinational, Multiregional, and Multicultural Contexts (Pages: 179-201)
CHAPTER 10 Smartphone Participation in Web Surveys: Choosing Between the Potential for Coverage, Nonresponse, and Measurement Error (Pages: 203-233)
CHAPTER 11 Survey Research and the Quality of Survey Data Among Ethnic Minorities (Pages: 235-252)
Section 3 : Data Collection and Data Processing Applications
CHAPTER 12 Measurement Error in Survey Operations Management: Detection, Quantification, Visualization, and Reduction (Pages: 253-277)
CHAPTER 13 Total Survey Error for Longitudinal Surveys (Pages: 279-298)
CHAPTER 14 Text Interviews on Mobile Devices (Pages: 299-318)
CHAPTER 15 Quantifying Measurement Errors in Partially Edited Business Survey Data (Pages: 319-337)
Section 4 : Evaluation and Improvement
CHAPTER 16 Estimating Error Rates in an Administrative Register and Survey Questions Using a Latent Class Model (Pages: 339-358)
CHAPTER 17 ASPIRE: An Approach for Evaluating and Reducing the Total Error in Statistical Products with Application to Registers and the National Accounts (Pages: 359-385)
CHAPTER 18 Classification Error in Crime Victimization Surveys: A Markov Latent Class Analysis (Pages: 387-412)
CHAPTER 19 Using Doorstep Concerns Data to Evaluate and Correct for Nonresponse Error in a Longitudinal Survey (Pages: 413-431)
CHAPTER 20 Total Survey Error Assessment for Sociodemographic Subgroups in the 2012 U.S. National Immunization Survey (Pages: 433-456)
CHAPTER 21 Establishing Infrastructure for the Use of Big Data to Understand Total Survey Error: Examples from Four Survey Research Organizations (Pages: 457-485)
Section 5 : Estimation and Analysis
CHAPTER 22 Analytic Error as an Important Component of Total Survey Error: Results from a Meta‐Analysis (Pages: 487-510)
CHAPTER 23 Mixed‐Mode Research: Issues in Design and Analysis (Pages: 511-530)
CHAPTER 24 The Effect of Nonresponse and Measurement Error on Wage Regression across Survey Modes: A Validation Study (Pages: 531-556)
CHAPTER 25 Errors in Linking Survey and Administrative Data (Pages: 557-573)
Index (Pages: 575-593)
WILEY SERIES IN SURVEY METHODOLOGY (Pages: b1-b3)

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