Assessing the Quality of Survey Data

General Information

Assessing the Quality of Survey Data Quote from the cover:



Table of Contents

Chapter 1: Conceptualizing data quality: Respondent attributes, study architecture and institutional practices

  1. Conceptualizing response quality
  2. Study architecture
  3. Institutional quality control practices
  4. Data screening methodology
  5. Chapter outline

Chapter 2: Empirical findings on quality and comparability of survey data

  1. Response quality
  2. Approaches to detecting systematic response errors
  3. Questionnaire architecture
  4. Cognitive maps in cross-cultural perspective
  5. Conclusion

Chapter 3: Statistical techniques for data screening

  1. Principal component analysis
  2. Categorical principal component analysis
  3. Multiple correspondence analysis
  4. Conclusion

Chapter 4: Institutional quality control practices

  1. Detecting procedural deficiencies
  2. Data duplication
  3. Detecting faked and partly faked interviews
  4. Data entry errors
  5. Conclusion

Chapter 5: Substantive or methodology-induced factors? A comparison of PCA, CatPCA and MCA solutions

  1. Descriptive analysis of personal feelings domain
  2. Rotation and structure of data
  3. Conclusion

Chapter 6: Item difficulty and response quality

  1. Descriptive analysis of political efficacy domain
  2. Detecting patterns with subset multiple correspondence analysis
  3. Moderator effects
  4. Conclusion

Chapter 7: Questionnaire architecture

  1. Fatigue effect
  2. Question order effects
  3. Measuring data quality: The dirty data index
  4. Conclusion

Chapter 8: Cognitive competencies and response quality

  1. Data and measures
  2. Response quality, task simplification, and complexity of cognitive maps
  3. Conclusion

Chapter 9: Conclusion