Good, fast, cheap: Pick two – Optimizing Sampling Strategies for Modern Survey Research |
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| Coordinator 1 | Professor Sabine Zinn (DIW-SOEP / Humboldt University Berlin) |
| Coordinator 2 | Dr Hans Walter Steinhauer (Socio-Economic Panel at DIW) |
Survey research is increasingly adapting to the demands of fast-paced environments where timely, reliable data is crucial, often within limited budgets. To meet these demands, researchers frequently use non-random sampling and online data collection, which provide quick results but may lack reliability. Traditional methods that ensure accuracy are slower and more costly, yet essential for scientific research and policymaking.
This session invites contributions on the practical use of sampling frames for generating random samples, such as population registers or geo-referenced databases. We are also interested in research on non-probability sampling methods, including data from social media, affordable access panels like Prolific, and respondent-driven sampling schemes. Our goal is to examine the pros and cons of these sampling strategies, focusing on coverage, bias, generalizability, cost, and speed.
We seek discussions on optimal sampling approaches tailored to specific study needs, where researchers must balance the urgency of obtaining rapid results with the need for high-quality studies that can inform policy recommendations.
We invite submissions on:
- Innovative sampling frames for social science surveys
- Combining different sampling frames to enhance data quality and timeliness
- Methods for improving accuracy and quick data access
- Cost analyses of various sampling strategies
- Experiences using fast-access data from web providers like Prolific and Respondi for social science research
Through these discussions, we aim to guide the development of more effective and efficient approaches to survey research in today’s fast-paced data environment.