This R package provides functions for improving the accuracy of school-level aggregate growth measures using Empirical Best Linear Prediction (EBLP). It uses student-level growth scores for particular years, grades, and subjects to compute simple average estimates and EBLPs of specified school-level aggregate growth targets. Estimated MSEs for both direct estimates and EBLPs are also provided. The details of the functions are described in Lockwood et al. (2022).
Reference: Lockwood, J. R., Castellano, K. E., & McCaffrey, D. F. (2022). Improving Accuracy and Stability of Aggregate Student Growth Measures Using Empirical Best Linear Prediction. Journal of Educational and Behavioral Statistics, 47(5), 544-575. https://doi.org/10.3102/10769986221101624
Install within the program R by using:
devtools:::install_github("EducationalTestingService/schoolgrowth")
library(schoolgrowth)
To run examples, use:
example(schoolgrowth)
To contribute to the package, please contact the package author Katherine Castellano at KEcastellano@ets.org.