Format:
1 online resource (627 pages)
Edition:
1st ed.
ISBN:
9781119041689
Series Statement:
Wiley Series in Survey Methodology Series
Note:
Intro -- Title Page -- Copyright Page -- Contents -- Notes on Contributors -- Preface -- Section 1 The Concept of TSE and the TSE Paradigm -- Chapter 1 The Roots and Evolution of the Total Survey Error Concept -- 1.1 Introduction and Historical Backdrop -- 1.2 Specific Error Sources and Their Control or Evaluation -- 1.3 Survey Models and Total Survey Design -- 1.4 The Advent of More Systematic Approaches Toward Survey Quality -- 1.5 What the Future Will Bring -- References -- Chapter 2 Total Twitter Error: Decomposing Public Opinion Measurement on Twitter from a Total Survey Error Perspective -- 2.1 Introduction -- 2.1.1 Social Media: A Potential Alternative to Surveys? -- 2.1.2 TSE as a Launching Point for Evaluating Social Media Error -- 2.2 Social Media: An Evolving Online Public Sphere -- 2.2.1 Nature, Norms, and Usage Behaviors of Twitter -- 2.2.2 Research on Public Opinion on Twitter -- 2.3 Components of Twitter Error -- 2.3.1 Coverage Error -- 2.3.2 Query Error -- 2.3.3 Interpretation Error -- 2.3.4 The Deviation of Unstructured Data Errors from TSE -- 2.4 Studying Public Opinion on the Twittersphere and the Potential Error Sources of Twitter Data: Two Case Studies -- 2.4.1 Research Questions and Methodology of Twitter Data Analysis -- 2.4.2 Potential Coverage Error in Twitter Examples -- 2.4.3 Potential Query Error in Twitter Examples -- 2.4.3.1 Implications of Including or Excluding RTs for Error -- 2.4.3.2 Implications of Query Iterations for Error -- 2.4.4 Potential Interpretation Error in Twitter Examples -- 2.5 Discussion -- 2.5.1 A Framework That Better Describes Twitter Data Errors -- 2.5.2 Other Subclasses of Errors to Be Investigated -- 2.6 Conclusion -- 2.6.1 What Advice We Offer for Researchers and Research Consumers -- 2.6.2 Directions for Future Research -- References -- Chapter 3 Big Data: A Survey Research Perspective
,
12.5.2.1 Dashboards and Paradata
,
3.1 Introduction -- 3.2 Definitions -- 3.2.1 Sources -- 3.2.2 Attributes -- 3.2.2.1 Volume -- 3.2.2.2 Variety -- 3.2.2.3 Velocity -- 3.2.2.4 Veracity -- 3.2.2.5 Variability -- 3.2.2.6 Value -- 3.2.2.7 Visualization -- 3.2.3 The Making of Big Data -- 3.3 The Analytic Challenge: From Database Marketing to Big Data and Data Science -- 3.4 Assessing Data Quality -- 3.4.1 Validity -- 3.4.2 Missingness -- 3.4.3 Representation -- 3.5 Applications in Market, Opinion, and Social Research -- 3.5.1 Adding Value through Linkage -- 3.5.2 Combining Big Data and Surveys in Market Research -- 3.6 The Ethics of Research Using Big Data -- 3.7 The Future of Surveys in a Data-Rich Environment -- References -- Chapter 4 The Role of Statistical Disclosure Limitation in Total Survey Error -- 4.1 Introduction -- 4.2 Primer on SDL -- 4.3 TSE-Aware SDL -- 4.3.1 Additive Noise -- 4.3.2 Data Swapping -- 4.4 Edit-Respecting SDL -- 4.4.1 Simulation Experiment -- 4.4.2 A Deeper Issue -- 4.5 SDL-Aware TSE -- 4.6 Full Unification of Edit, Imputation, and SDL -- 4.7 ``Big Data´´ Issues -- 4.8 Conclusion -- Acknowledgments -- References -- Section 2 Implications for Survey Design -- Chapter 5 The Undercoverage-Nonresponse Tradeoff -- 5.1 Introduction -- 5.2 Examples of the Tradeoff -- 5.3 Simple Demonstration of the Tradeoff -- 5.4 Coverage and Response Propensities and Bias -- 5.5 Simulation Study of Rates and Bias -- 5.5.1 Simulation Setup -- 5.5.2 Results for Coverage and Response Rates -- 5.5.3 Results for Undercoverage and Nonresponse Bias -- 5.5.3.1 Scenario 1 -- 5.5.3.2 Scenario 2 -- 5.5.3.3 Scenario 3 -- 5.5.3.4 Scenario 4 -- 5.5.3.5 Scenario 7 -- 5.5.4 Summary of Simulation Results -- 5.6 Costs -- 5.7 Lessons for Survey Practice -- References -- Chapter 6 Mixing Modes: Tradeoffs Among Coverage, Nonresponse, and Measurement Error Roger Tourangeau -- 6.1 Introduction
,
6.2 The Effect of Offering a Choice of Modes -- 6.3 Getting People to Respond Online -- 6.4 Sequencing Different Modes of Data Collection -- 6.5 Separating the Effects of Mode on Selection and Reporting -- 6.5.1 Conceptualizing Mode Effects -- 6.5.2 Separating Observation from Nonobservation Error -- 6.5.2.1 Direct Assessment of Measurement Errors -- 6.5.2.2 Statistical Adjustments -- 6.5.2.3 Modeling Measurement Error -- 6.6 Maximizing Comparability Versus Minimizing Error -- 6.7 Conclusions -- References -- Chapter 7 Mobile Web Surveys: A Total Survey Error Perspective -- 7.1 Introduction -- 7.2 Coverage -- 7.3 Nonresponse -- 7.3.1 Unit Nonresponse -- 7.3.2 Breakoffs -- 7.3.3 Completion Times -- 7.3.4 Compliance with Special Requests -- 7.4 Measurement Error -- 7.4.1 Grouping of Questions -- 7.4.1.1 Question-Order Effects -- 7.4.1.2 Number of Items on a Page -- 7.4.1.3 Grids versus Item-By-Item -- 7.4.2 Effects of Question Type -- 7.4.2.1 Socially Undesirable Questions -- 7.4.2.2 Open-Ended Questions -- 7.4.3 Response and Scale Effects -- 7.4.3.1 Primacy Effects -- 7.4.3.2 Slider Bars and Drop-Down Questions -- 7.4.3.3 Scale Orientation -- 7.4.4 Item Missing Data -- 7.5 Links Between Different Error Sources -- 7.6 The Future of Mobile web Surveys -- References -- Chapter 8 The Effects of a Mid-Data Collection Change in Financial Incentives on Total Survey Error in the National Survey of Famil... -- 8.1 Introduction -- 8.2 Literature Review: Incentives in Face-to-Face Surveys -- 8.2.1 Nonresponse Rates -- 8.2.2 Nonresponse Bias -- 8.2.3 Measurement Error -- 8.2.4 Survey Costs -- 8.2.5 Summary -- 8.3 Data and Methods -- 8.3.1 NSFG Design: Overview -- 8.3.2 Design of Incentive Experiment -- 8.3.3 Variables -- 8.3.4 Statistical Analysis -- 8.4 Results -- 8.4.1 Nonresponse Error -- 8.4.2 Sampling Error and Costs -- 8.4.3 Measurement Error
,
8.5 Conclusion -- 8.5.1 Summary -- 8.5.2 Recommendations for Practice -- References -- Chapter 9 A Total Survey Error Perspective on Surveys in Multinational, Multiregional, and Multicultural Contexts -- 9.1 Introduction -- 9.2 TSE in Multinational, Multiregional, and Multicultural Surveys -- 9.3 Challenges Related to Representation and Measurement Error Components in Comparative Surveys -- 9.3.1 Representation Error -- 9.3.1.1 Coverage Error -- 9.3.1.2 Sampling Error -- 9.3.1.3 Unit Nonresponse Error -- 9.3.1.4 Adjustment Error -- 9.3.2 Measurement Error -- 9.3.2.1 Validity -- 9.3.2.2 Measurement Error - The Response Process -- 9.3.2.3 Processing Error -- 9.4 QA and QC in 3MC Surveys -- 9.4.1 The Importance of a Solid Infrastructure -- 9.4.2 Examples of QA and QC Approaches Practiced by Some 3MC Surveys -- 9.4.3 QA/QC Recommendations -- References -- Chapter 10 Smartphone Participation in Web Surveys: Choosing Between the Potential for Coverage, Nonresponse, and Measurement Error -- 10.1 Introduction -- 10.1.1 Focus on Smartphones -- 10.1.2 Smartphone Participation: Web-Survey Design Decision Tree -- 10.1.3 Chapter Outline -- 10.2 Prevalence of Smartphone Participation in Web Surveys -- 10.3 Smartphone Participation Choices -- 10.3.1 Disallowing Smartphone Participation -- 10.3.2 Discouraging Smartphone Participation -- 10.4 Instrument Design Choices -- 10.4.1 Doing Nothing -- 10.4.2 Optimizing for Smartphones -- 10.5 Device and Design Treatment Choices -- 10.5.1 PC/Legacy versus Smartphone Designs -- 10.5.2 PC/Legacy versus PC/New -- 10.5.3 Smartphone/Legacy versus Smartphone/New -- 10.5.4 Device and Design Treatment Options -- 10.6 Conclusion -- 10.7 Future Challenges and Research Needs -- Appendix 10.A: Data Sources -- A.1 Market Strategies (17 studies) -- A.2 Experimental Data from Market Strategies International
,
A.3 Sustainability Cultural Indicators Program (SCIP) -- A.4 Army Study to Assess Risk and Resilience in Service members (STARRS) -- A.5 Panel Study of Income Dynamics Childhood Retrospective Circumstances Study (PSID-CRCS) -- Appendix 10.B: Smartphone Prevalence in Web Surveys -- Appendix 10.C: Screen Captures from Peterson and others (2013) Experiment -- Appendix 10.D: Survey Questions Used in the Analysis of the Peterson and others (2013) Experiment -- References -- Chapter 11 Survey Research and the Quality of Survey Data Among Ethnic Minorities -- 11.1 Introduction -- 11.2 On the Use of the Terms Ethnicity and Ethnic Minorities -- 11.3 On the Representation of Ethnic Minorities in Surveys -- 11.3.1 Coverage of Ethnic Minorities -- 11.3.2 Factors Affecting Nonresponse Among Ethnic Minorities -- 11.3.3 Postsurvey Adjustment Issues Related to Surveys Among Ethnic Minorities -- 11.4 Measurement Issues -- 11.4.1 The Tradeoff When Using Response-Enhancing Measures -- 11.5 Comparability, Timeliness, and Cost Concerns -- 11.5.1 Comparability -- 11.5.2 Timeliness and Cost Considerations -- 11.6 Conclusion -- References -- Section 3 Data Collection and Data Processing Applications -- Chapter 12 Measurement Error in Survey Operations Management: Detection, Quantification, Visualization, and Reduction -- 12.1 TSE Background on Survey Operations -- 12.2 Better and Better: Using Behavior Coding (CARIcode) and Paradata to Evaluate and Improve Question (Specification) Erro... -- 12.2.1 CARI Coding at Westat -- 12.2.2 CARI Experiments -- 12.3 Field-Centered Design: Mobile App for Rapid Reporting and Management -- 12.3.1 Mobile App Case Study -- 12.3.2 Paradata Quality -- 12.4 Faster and Cheaper: Detecting Falsification With GIS Tools -- 12.5 Putting It All Together: Field Supervisor Dashboards -- 12.5.1 Dashboards in Operations -- 12.5.2 Survey Research Dashboards
Additional Edition:
Print version Biemer, Paul P. Total Survey Error in Practice Newark : John Wiley & Sons, Incorporated,c2017 ISBN 9781119041672
Language:
English
Keywords:
Electronic books
;
Electronic books
URL:
FULL
((OIS Credentials Required))
URL:
FULL
((OIS Credentials Required))
Bookmarklink
