ESRA 2027 sessions by theme
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Innovations in Nonprobability Sampling and Data Integration |
| Coordinator 1 | Dr Katherine Irimata (National Center for Health Statistics) |
| Coordinator 2 | Dr Jon Krosnick (Stanford University) |
| Coordinator 3 | Dr Frauke Kreuter (University of Maryland; Ludwig-Maximilians-University of Munich) |
Session Details
Nonprobability samples often exhibit higher bias and lower data quality than probability samples due to a variety of factors including coverage and sampling errors. Despite these limitations, nonprobability samples are inexpensive, fast to collect, and increasingly prevalent. In addition, they can capture valuable information that may not be available from other sources. Recent studies have advanced our understanding of differences between probability and nonprobability samples and developed methods for extracting reliable information from nonprobability data.
This session will highlight new findings and innovative approaches for working with nonprobability samples and integrating probability and nonprobability data. We invite methodological and applied contributions that address the challenges and opportunities of using nonprobability samples and provide clear guidance for survey practitioners. Topics of interest include, but are not limited to:
• Data quality assessment
• Characterizing differences between probability and nonprobability respondents
• Weighting and calibration methods
• Estimation methods that account for bias, including small area estimation approaches
• Approaches for integrating probability and nonprobability samples
• Practical applications demonstrating the use of nonprobability data
