Aggregating administrative and survey data from a multi-site randomized controlled trial on intensive advising for low-income high-school students. It was used to analyze the impact of advising on bachelor's degree attainment and initial college enrollment quality.
Use Cases
- Apply causal forest methods to analyze the effect of intensive advising on degree attainment outcomes.
- Analyze pre-advising college preferences data to understand their role in determining initial enrollment quality.
- Model the relationship between college choice strategies and economic mobility for lower-income students.
Strengths
- Data originates from a multi-site randomized controlled trial, providing a basis for causal inference.
- Includes unique data on pre-advising college preferences, a key variable for analysis.
Limitations
- The specific sample size (row count) and number of variables (columns) are unknown.
- Data is focused on low-income high-school students, which may limit generalizability to other populations.
Provenance
- Source
- ICPSR Harvested Dataverse
- Collection Method
- Combined administrative and survey data from a multi-site randomized controlled trial.
- Time Range
- null
- Freshness
- null
- Geography
- null