|Title:||Improving Methods for Policy Impact Evaluation with Group Panel Data in Education Research|
|Principal Investigator:||Feller, Avi||Awardee:||University of California, Berkeley|
|Program:||Statistical and Research Methodology in Education [Program Details]|
|Award Period:||3 years (07/01/2020 – 06/30/2023)||Award Amount:||$896,026|
|Type:||Methodological Innovation||Award Number:||R305D200010|
Co-Principal Investigators: Miratrix, Luke; Rothstein, Jesse
When a randomized control trial is infeasible in an education setting, researchers can use quasi-experimental research designs. A commonly used approach is to use repeated observations of aggregate data, known as group panel data, before and after a new policy or intervention is put in place. To estimate the effects, researchers typically rely on either a comparative interrupted time series (CITS) or, increasingly, the synthetic control method (SCM), but there is not a clear set of best practices for implementing these designs or for analyzing the data from them. The purpose of this grant is to develop such guidance and to develop a new estimation approach which combines CITS and SCM.
The research team will conduct simulation studies and multiple within-study comparisons using real data. They will then work with applied researchers to develop and clarify clear study guidelines and reporting standards for CITS, SCM, and the newly developed combination of them. The research team will also create user-friendly software for conducting analyses of data from these designs. They will disseminate their guidelines, reporting standards, and software through seminars, short courses, conference presentations, and peer-reviewed journal manuscripts.