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Total Survey Error in Practice : Improving Quality in the Era of Big Data.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , , , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Somerset :
John Wiley & Sons, Incorporated,
2016.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 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 Analysis2.4.2 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 Perspective3.1 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 Data3.7 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.