Project Activities
The research team will first develop the models and their causal estimands. They will then develop software for estimating model parameters and conducting diagnostic tests of the assumptions made by the models. After the software is ready, the researchers will run a real-data demonstration of the RD model with multilevel latent variable measurement models, using data from the Oregon English Language Learners Program and the Baltimore City Public Schools Gifted and Advanced Learning Program.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
The research team will also develop a user-friendly version of the software in R, with supporting instructional materials. Other products from the grant will include workshops for using the software and peer-reviewed journal manuscripts in methodological and applied journals.
Publications:
Han, Y., Yang, J. S., & Liu, Y. (2024). Assessing Item Fit Using Expected Score Curve Under Restricted Recalibration. Journal of Educational and Behavioral Statistics, 10769986241268604.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
