Project Activities
The researchers will use Monte Carlo simulations based on actual CRT design features to gauge the comparative accuracy of the estimators and their standard errors. The research team will also conduct secondary analyses of real data from several CRTs in order to illustrate differences in practice among the numerical values of the estimators and standard errors, as well as the interpretations of the estimators, given their underlying estimands.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
The research team will publish a synthesis of the results online and as a peer-reviewed journal manuscript. The researchers will also publish a user-friendly R package that will be able to conduct analyses to provide all the estimators investigated as part of the grant work. They will present research findings and the software package at conferences and at workshops on using the software.
Publications:
Gilbert, J. B., Himmelsbach, Z., Soland, J., Joshi, M., & Domingue, B. W. (2024). Estimating heterogeneous treatment effects with item-level outcome data: Insights from item response theory. arXiv preprint arXiv:2405.00161.
Gilbert, J. B., Himmelsbach, Z., Soland, J., Joshi, M., & Domingue, B. W. (2025). Estimating heterogeneous treatment effects with item‐level outcome data: Insights from Item Response Theory. Journal of Policy Analysis and Management, 44(4), 1417-1449.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
