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Expert Disagreement: Mean vs Median Responses Lead to Different Survey Outcomes
Insights from the Field
mean response
median response
modal response
EU integration
expert surveys
Methodology
PSR&M
9 R files
4 datasets
1 text files
Dataverse
When Experts Disagree: Response Aggregation and Its Consequences in Expert Surveys was authored by Jonathan Slapin, René Lindstädt and Sven-Oliver Proksch. It was published by Cambridge in PSR&M in 2020.

### Expert Surveys & Measurement Challenges

Political scientists frequently employ expert surveys to uncover the intrinsic traits of political entities. However, experts often disagree due to varying levels of information and analytical capability.

### Proposed Solutions for Better Assessment

This article addresses how to effectively handle this uncertainty:

* Assessing experts' predictive abilities (how well they judge latent positions)

* Developing robust methods to combine their diverse responses

### Case Study: EU Integration & Party Politics Survey

The authors analyze prominent expert survey data from the literature focusing on party politics and European Union integration. This real-world application highlights practical consequences of different aggregation approaches.

### Monte Carlo Simulation Findings

Using simulation, we show that:

* Aggregating responses using median or modal values outperforms mean averaging in most scenarios

These methods produce more accurate aggregated estimates despite expert disagreement.

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Political Science Research & Methods
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