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Improving Surveys with Paradata: Analytic Uses of Process Information

Book Description

Explore the practices and cutting-edge research on the new and exciting topic of paradata

Paradata are measurements related to the process of collecting survey data.

Improving Surveys with Paradata: Analytic Uses of Process Information is the most accessible and comprehensive contribution to this up-and-coming area in survey methodology.

Featuring contributions from leading experts in the field, Improving Surveys with Paradata: Analytic Uses of Process Information introduces and reviews issues involved in the collection and analysis of paradata. The book presents readers with an overview of the indispensable techniques and new, innovative research on improving survey quality and total survey error. Along with several case studies, topics include:

  • Using paradata to monitor fieldwork activity in face-to-face, telephone, and web surveys

  • Guiding intervention decisions during data collection

  • Analysis of measurement, nonresponse, and coverage error via paradata

Providing a practical, encompassing guide to the subject of paradata, the book is aimed at both producers and users of survey data. Improving Surveys with Paradata: Analytic Uses of Process The book also serves as an excellent resource for courses on data collection, survey methodology, and nonresponse and measurement error.

Table of Contents

  1. Cover
  2. Wiley Series in Survey Methodology
  3. Title Page
  4. Copyright
  5. Preface
  6. Contributors
  7. Acronyms
  8. Chapter 1: Improving Surveys with Paradata: Introduction
    1. 1.1 INTRODUCTION
    2. 1.2 PARADATA AND METADATA
    3. 1.3 AUXILIARY DATA AND PARADATA
    4. 1.4 PARADATA IN THE TOTAL SURVEY ERROR FRAMEWORK
    5. 1.5 PARADATA IN SURVEY PRODUCTION
    6. 1.6 SPECIAL CHALLENGES IN THE COLLECTION AND USE OF PARADATA
    7. 1.7 FUTURE OF PARADATA
    8. REFERENCES
  9. Part I: Paradata and Survey Errors
    1. Chapter 2: Paradata for Nonresponse Error Investigation
      1. 2.1 INTRODUCTION
      2. 2.2 SOURCES AND NATURE OF PARADATA FOR NONRESPONSE ERROR INVESTIGATION
      3. 2.3 NONRESPONSE RATES AND NONRESPONSE BIAS
      4. 2.4 PARADATA AND RESPONSIVE DESIGNS
      5. 2.5 PARADATA AND NONRESPONSE ADJUSTMENT
      6. 2.6 ISSUES IN PRACTICE
      7. 2.7 SUMMARY AND TAKE HOME MESSAGES
      8. REFERENCES
    2. Chapter 3: Collecting Paradata for Measurement Error Evaluations
      1. 3.1 INTRODUCTION
      2. 3.2 PARADATA AND MEASUREMENT ERROR
      3. 3.3 TYPES OF PARADATA
      4. 3.4 DIFFERENCES IN PARADATA BY MODES
      5. 3.5 TURNING PARADATA INTO DATASETS
      6. 3.6 SUMMARY
      7. FUNDING NOTE
      8. REFERENCES
    3. Chapter 4: Analyzing Paradata to Investigate Measurement Error
      1. 4.1 INTRODUCTION
      2. 4.2 REVIEW OF EMPIRICAL LITERATURE ON THE USE OF PARADATA FOR MEASUREMENT ERROR INVESTIGATION
      3. 4.3 ANALYZING PARADATA
      4. 4.4 FOUR EMPIRICAL EXAMPLES
      5. 4.5 CAUTIONS
      6. 4.6 CONCLUDING REMARKS
      7. REFERENCES
    4. Chapter 5: Paradata for Coverage Research
      1. 5.1 INTRODUCTION
      2. 5.2 HOUSING UNIT FRAMES
      3. 5.3 TELEPHONE NUMBER FRAMES
      4. 5.4 HOUSEHOLD ROSTERS
      5. 5.5 POPULATION REGISTERS
      6. 5.6 SUBPOPULATION FRAMES
      7. 5.7 WEB SURVEYS
      8. 5.8 CONCLUSION
      9. ACKNOWLEDGMENTS
      10. REFERENCES
  10. Part II: Paradata in Survey Production
    1. Chapter 6: Design and Management Strategies for Paradata-Driven Responsive Design: Illustrations from the 2006--2010 National Survey of Family Growth
      1. 6.1 INTRODUCTION
      2. 6.2 FROM REPEATED CROSS-SECTION TO CONTINUOUS DESIGN
      3. 6.3 PARADATA DESIGN
      4. 6.4 KEY DESIGN CHANGE 1: A NEW EMPLOYMENT MODEL
      5. 6.5 KEY DESIGN CHANGE 2: FIELD EFFICIENT SAMPLE DESIGN
      6. 6.6 KEY DESIGN CHANGE 3: REPLICATE SAMPLE DESIGN
      7. 6.7 KEY DESIGN CHANGE 4: RESPONSIVE DESIGN SAMPLING OF NONRESPONDENTS IN A SECOND PHASE
      8. 6.8 KEY DESIGN CHANGE 5: ACTIVE RESPONSIVE DESIGN INTERVENTIONS
      9. 6.9 CONCLUDING REMARKS
      10. REFERENCES
    2. Chapter 7: Using Paradata-Driven Models to Improve Contact Rates in Telephone and Face-to-Face Surveys
      1. 7.1 INTRODUCTION
      2. 7.2 BACKGROUND
      3. 7.3 THE SURVEY SETTING
      4. 7.4 EXPERIMENTS: DATA AND METHODS
      5. 7.5 EXPERIMENTS: RESULTS
      6. 7.6 DISCUSSION
      7. REFERENCES
    3. Chapter 8: Using Paradata to Study Response to Within-Survey Requests
      1. 8.1 INTRODUCTION
      2. 8.2 CONSENT TO LINK SURVEY AND ADMINISTRATIVE RECORDS
      3. 8.3 CONSENT TO COLLECT BIOMEASURES IN POPULATION-BASED SURVEYS
      4. 8.4 SWITCHING DATA COLLECTION MODES
      5. 8.5 INCOME ITEM NONRESPONSE AND QUALITY OF INCOME REPORTS
      6. 8.6 SUMMARY
      7. ACKNOWLEDGMENTS
      8. REFERENCES
    4. Chapter 9: Managing Data Quality Indicators with Paradata Based Statistical Quality Control Tools: The Keys to Survey Performance
      1. 9.1 INTRODUCTION
      2. 9.2 DEFINING AND CHOOSING KEY PERFORMANCE INDICATORS (KPIs)
      3. 9.3 KPI DISPLAYS AND THE ENDURING INSIGHT OF WALTER SHEWHART
      4. 9.4 IMPLEMENTATION STEPS FOR SURVEY ANALYTIC QUALITY CONTROL WITH PARADATA CONTROL CHARTS
      5. 9.5 DEMONSTRATING A METHOD FOR IMPROVING MEASUREMENT PROCESS QUALITY INDICATORS
      6. 9.6 REFLECTIONS ON SPC, VISUAL DATA DISPLAYS, AND CHALLENGES TO QUALITY CONTROL AND ASSURANCE WITH SURVEY ANALYTICS
      7. 9.7 SOME ADVICE ON USING CHARTS
      8. APPENDIX
      9. ACKNOWLEDGMENTS
      10. REFERENCES
    5. Chapter 10: Paradata as Input to Monitoring Representativeness and Measurement Profiles: A Case Study of the Dutch Labour Force Survey
      1. 10.1 INTRODUCTION
      2. 10.2 MEASUREMENT PROFILES
      3. 10.3 TOOLS FOR MONITORING NONRESPONSE AND MEASUREMENT PROFILES
      4. 10.4 MONITORING AND IMPROVING RESPONSE: A DEMONSTRATION USING THE LFS
      5. 10.5 INCLUDING PARADATA OBSERVATIONS ON HOUSEHOLDS AND PERSONS
      6. 10.6 GENERAL DISCUSSION
      7. 10.7 TAKE HOME MESSAGES
      8. ACKNOWLEDGMENTS
      9. REFERENCES
  11. Part III: Special Challenges
    1. Chapter 11: Paradata in Web Surveys
      1. 11.1 SURVEY DATA TYPES
      2. 11.2 COLLECTION OF PARADATA
      3. 11.3 TYPOLOGY OF PARADATA IN WEB SURVEYS
      4. 11.4 USING PARADATA TO CHANGE THE SURVEY IN REAL TIME: ADAPTIVE SCRIPTING
      5. 11.5 PARADATA IN ONLINE PANELS
      6. 11.6 SOFTWARE TO COLLECT PARADATA
      7. 11.7 ANALYSIS OF PARADATA: LEVELS OF AGGREGATION
      8. 11.8 PRIVACY AND ETHICAL ISSUES IN COLLECTING WEB SURVEY PARADATA
      9. 11.9 SUMMARY AND CONCLUSIONS ON PARADATA IN WEB SURVEYS
      10. REFERENCES
    2. Chapter 12: Modeling Call Record Data: Examples from Cross-Sectional and Longitudinal Surveys
      1. 12.1 INTRODUCTION
      2. 12.2 CALL RECORD DATA
      3. 12.3 MODELING APPROACHES
      4. 12.4 ILLUSTRATION OF CALL RECORD DATA ANALYSIS USING TWO EXAMPLE DATASETS
      5. 12.5 SUMMARY
      6. ACKNOWLEDGMENTS
      7. REFERENCES
    3. Chapter 13: Bayesian Penalized Spline Models for Statistical Process Monitoring of Survey Paradata Quality Indicators
      1. 13.1 INTRODUCTION
      2. 13.2 OVERVIEW OF SPLINES
      3. 13.3 PENALIZED SPLINES AS LINEAR MIXED MODELS
      4. 13.4 BAYESIAN METHODS
      5. 13.5 EXTENSIONS
      6. APPENDIX
      7. REFERENCES
    4. Chapter 14: The Quality of Paradata: A Literature Review
      1. 14.1 INTRODUCTION
      2. 14.2 EXISTING STUDIES EXAMINING THE QUALITY OF PARADATA
      3. 14.3 POSSIBLE MECHANISMS LEADING TO ERROR IN PARADATA
      4. 14.4 TAKE HOME MESSAGES
      5. REFERENCES
    5. Chapter 15: The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study
      1. 15.1 INTRODUCTION
      2. 15.2 DESIGN OF SIMULATION STUDIES
      3. 15.3 SIMULATION RESULTS
      4. 15.4 TAKE HOME MESSAGES
      5. 15.5 FUTURE RESEARCH
      6. REFERENCES
  12. Index