Survey science is driven to maximize data quality and reduce Total Survey Error (TSE). At the same time, survey methodologists have ethical and professional obligations to protect the privacy of respondents and ensure their capacity to provide informed consent for their participation, for data linkage, passive data collection, and the archiving of replication data. We have learned, however, that both sensitive topics and the consent process can contribute to errors of representation and errors of measurement. These compound threats to data quality that arise due to broader concerns about privacy, the intrusiveness of surveys, and the increasing number of participation requests directed to the same respondents. This article critically assesses the extant literature on these topics - including six original articles in this issue - by viewing these challenges through the lens of the TSE framework. This helps unify several distinct research programs and provides the foundation for new research and for practical innovations that will improve data quality.
All Science Journal Classification (ASJC) codes
- Sociology and Political Science
- Social Sciences(all)
- History and Philosophy of Science