Duration of the Workshop:
2,5 hours
Target Groups:
This workshop is intended for students, researchers, and practitioners who work with nonprobability sample surveys and seek to assess data quality and explore methods for drawing inferences.
Is the workshop geared at an exclusively German or an international audience?
International audience (material will be in English)
Workshop Language:
English.
Description of the content of the workshop:
Academic and market researchers often rely on opt-in (volunteer) online panels to collect survey data. These panels allow for the rapid collection of responses, resulting in large datasets at a relatively low cost. While this approach is convenient and cost-effective, it has a major limitation: making inferences about the target population is not straightforward. The issue is that the sample is non-probabilistic; the panel consists of volunteers who self-select themselves, introducing selection bias. Addressing this bias requires statistical adjustments under strong assumptions.
In this workshop, we will discuss methods for making inference using nonprobability samples, focusing on how to:
• Identify challenges related to data quality and errors
• Design research projects based on nonprobability sample surveys
• Select appropriate methodologies to address selection bias
• Acknowledge the limitations of these methodologies
The workshop will include case studies from existing literature and practical exercises in R. Participants do not need prior knowledge of R. An online interactive page will be provided with explanations, code and results.
Goals of the workshop: Learn how to:
• Identify challenges related to data quality and errors
• Design research projects based on nonprobability sample surveys
• Select appropriate methodologies to address selection bias
• Acknowledge the limitations of these methodologies
Necessary prior knowledge of participants:
Participants should have basic pre-existing knowledge about survey methodology and statistics
.Literature that participants need to read for preparation
Participants can watch this video by the Pew Reserch Center about nonprobality surveys: https://www.pewresearch.org/short-reads/2018/08/06/what-are-nonprobability-surveys/
Recommended additional literature
• Mercer, A., Lau, A., & Kennedy, C. (2018). For weighting online opt-in samples, what matters most? Pew Research Center report. https://www.pewresearch.org/methods/2018/01/26/for-weighting-online-opt-in-samples-what-matters-most/
• Salvatore, C. (2023). Inference with non-probability samples and survey data integration: a science mapping study. Metron, 81(1), 83-107. https://link.springer.com/article/10.1007/s40300-023-00243-6
• Mercer, A. W., Kreuter, F., Keeter, S., & Stuart, E. A. (2017). Theory and practice in nonprobability surveys: parallels between causal inference and survey inference. Public Opinion Quarterly, 81. https://academic.oup.com/poq/article/81/S1/250/3749176
Additional references will be available in the slides
Information about the instructors:
Dr. Camilla Salvatore works as an assistant professor at the department of Methodology and Statistics at Utrecht University, where she specializes in survey research. Her interests include inference with nonprobability samples, survey weighting, nonresponse, the use of digital trace data and their integration with surveys. https://www.uu.nl/medewerkers/CSalvatore
Will participants need to bring their own devices in order to be able to access the Internet?
online workshop
