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R package for more accurate school-level aggregate growth measures using Empirical Best Linear Prediction (EBLP)

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EducationalTestingService/schoolgrowth

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SCHOOLGROWTH

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

INSTALLATION

Install within the program R by using: devtools:::install_github("EducationalTestingService/schoolgrowth") library(schoolgrowth)

EXAMPLES

To run examples, use: example(schoolgrowth)

CONTRIBUTING TO THE PACKAGE

To contribute to the package, please contact the package author Katherine Castellano at [email protected].

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R package for more accurate school-level aggregate growth measures using Empirical Best Linear Prediction (EBLP)

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