Statistical Methods and the Improvement of Data Quality

Contributors

Preface

Acknowledgments

Errors and Other Limitations of Surveys


1. Introduction


2. The Data Collection System Considered: A Survey


3. An Inherent Limitation


4. Errors in Surveys


5. The Formal Basis for Comprehensive Quality Control


6. Quality Control of the Survey Design


7. Quality Control of the Survey Operations

References

A Frame on Frames: An Annotated Bibliography


1. Introduction and Definition of a Frame


2. Construction of the Sampling Frame


3. Area Frames


4. Imperfect Frames


5. Sampling from Imperfect List Frames


6. Multiple Frame Surveys

The Annotated Bibliography

Data Collection for Details over Space and Time


1. Introduction


2. Samples and Censuses


3. Samples Connected with Censuses


4. Data from Registers


5. A Brief Historical Overview of Censuses


6. Postcensal Estimates for Domains


7. Design and Estimation for Domains


8. Purposes and Designs for Periodic Samples


9. Rolling Samples


10. Panels with Rolling Samples


11. Summary

References

Response Effects to Behavior and Attitude Questions


1. Introduction


2. Non-Threatening Behavior Questions


3. Reducing Memory Error


4. The Length of Questions


5. Threatening Behavioral Questions


6. The Magnitude of Errors in Threatening Questions


7. Determining the Perceived Level of Threat


8. Methods for Improving the Quality of Reporting of Threatening Questions


9. The Use of Familiar Words


10. Deliberately Loading the Question


11. Time Frame for Socially Undesirable and Desirable Behavior


12. Non-Interview Methods


13. Attitudinal Questions


14. Summary

References

Error Profiles: Uses and Abuses


1. Introduction


2. How to Develop Error Profiles


3. How to Use Error Profiles

References

Principles and Methods for Handling Outliers in Data Sets


1. Introduction


2. Some Basic Considerations for Univariate Samples


3. Multivariate Outliers


4. Outliers in Linear Models


5. Implications of the Data Collecting Mechanism for the Processing of Outliers

References

Influence Functions, Outlier Detection, and Data Editing


1. Introduction


2. Multivariate Outliers


3. Influence Functions


4. Form 4 Application


5. Inventory Difference Data Application


6. The Use of Influence Functions for Imputation

References

Using Exploratory Data Analysis to Monitor Socio-Economic Data Quality in Developing Countries


1. Introduction


2. The Problem


3. Exploratory Data Analysis


4. Conclusion

References

Application of Pattern Recognition Techniques to Data Analysis


1. Introduction


2. Heuristic Approach


3. Decision-Theoretic Approach


4. Syntactic Approach


5. Summary

References

Can Automatic Data Editing be Justified? One Person's Opinion


1. Introduction


2. The General Editing Procedure


3. Automatic Data Editing


4. Justifiability of Automatic Data Editing


5. Directions for Further Research

References

Missing Data in Large Data Sets


1. Introduction


2. Common Incomplete Data Problems


3. Methods for Handling Incomplete Data


4. General Data Patterns: The EM Algorithm


5. Multiple Imputation


6. Conclusion

References

Reducing the Cost of Studying Survey Measurement Error: Is a Laboratory Approach the Answer?


1. Introduction


2. Measurement Error Models


3. The Pearson Laboratory Experiment


4. Considerations for the Laboratory Experiment Approach


5. Summary

References

The Implication of Sample Design on Survey Data Analysis


1. Introduction


2. Types of Data Collection Systems


3. Sample Design Effects on Finite Population Inference


4. Examples of Survey Data Analysis and Effects of Design

References

An Approach to an Evaluation of the Quality of Motor Gasoline Prices


1. Introduction


2. Background


3. Internal Assessment


4. External Comparisons


5. Summary of Findings


6. General Conclusions Relative to the Quality of Data Collection Systems

References

Health and Mortality Study Error Detection, Reporting, and Resolution System


1. Overview


2. Types of Errors Reported


3. System Description


4. Summary

References

On Using Exploratory Data Analysis as an Aid in Modeling and Statistical Forecasting


1. Introduction


2. Overview


3. The Wharton Assessment of STIFS


4. The GLOBUS Project


5. Concluding Remarks

References

Index