Probability vs. non-probability online surveys: challenging traditional assumptions in research methodology

The Research Question
While academic research has traditionally favored probability-based sampling methods, non-probability online panels have gained significant traction in recent years due to their cost-effectiveness and accessibility. But what are we sacrificing in terms of data quality when we make this trade-off? Dr. Partheymüller's study tackles this question head-on.

Methodology

• The research compares two distinct online surveys conducted after Austria's 2024 parliamentary election:
• The probability-based Digitize! Online Panel Survey
• The non-probability AUTNES Online Panel Survey
• The comparison examines three critical dimensions:
• Accuracy – how well each survey aligns with external benchmarks like demographic data and actual election outcomes
• Response Quality – measuring factors like participant attentiveness, response consistency, and potential biases
• Survey Professionalism – analyzing response time, participation frequency, device preferences, and digital literacy

Unexpected Findings
The results challenge conventional wisdom in several ways:

Accuracy
Surprisingly, the non-probability sample demonstrated somewhat higher accuracy, particularly regarding political characteristics such as turnout. This unexpected outcome appears to stem from education bias in the probability sample, where self-selection played a significant role.

Response Quality
Contrary to concerns about non-probability panels, both survey types showed comparable results in attentiveness and internal consistency measures, with no significant differences observed.

Survey Professionalism
The non-probability online panel exhibited higher overall professionalism, with respondents showing a somewhat stronger motivation from financial incentives and participating in more surveys generally.

Implications for Research Practice
These findings have important implications for researchers:
Non-probability surveys continue to gain popularity due to their practical advantages in cost, speed, and accessibility
Concerns about their accuracy and response quality may be somewhat overstated based on this evidence
However, major comparative projects like CSES still maintain strict probability-based sample requirements, indicating ongoing methodological debates

Moving Forward
While probability-based sampling remains the gold standard theoretically, Dr. Partheymüller's research suggests non-probability surveys can provide valuable research insights when:

• Probability-based samples aren't feasible

• Researchers provide transparent documentation

• Rigorous validation processes are implemented

• Context-specific quality assessments are conducted continuously

As research methodologies continue to evolve in our digital age, this study provides important evidence that may help reshape best practices in survey research design and implementation. Watch video summary about research here.

About the speaker:
Dr. Julia Partheymüller is Senior Scientist at the Department of Government and a member of the Vienna Center for Electoral Research (VieCER). She previously worked as DAAD lecturer at the University of Essex and was part of the team of the German Longitudinal Election Study (GLES) at the Mannheim Centre for European Social Research (MZES) at the University of Mannheim. She holds a doctoral degree in Social Sciences from the University of Mannheim and has studied Political Science at the Free University Berlin and University of Hamburg.

Check Dr. Julia Partheymüller website for more information.