A conjoint experiment dataset with 9,895 respondents examines how the partisan composition of the U.S. Supreme Court affects public evaluations of nominees. The data was produced by Yusaku Horiuchi and is hosted by the Journal of Law and Courts Dataverse. It was last updated in May 2026.
Use Cases
- Analyze partisan bias in nominee evaluations based on the experimental design.
- Model the effect of a Court's partisan composition on respondent choices.
- Study threat-based political psychology using the described experimental conditions.
Strengths
- Data is from a preregistered conjoint experiment, which suggests a structured research design.
- The experiment includes 9,895 respondents, providing a substantial sample size.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- Journal of Law and Courts Dataverse
- Collection Method
- Preregistered conjoint experiment
- Freshness
- Last updated 2026-05-20 22:40:41; freshness should be verified.
- Geography
- United States