Sources & Software Citations

Data Sources

  • Louisiana Department of Education: LEAP 2025 Assessment Master Results (2018–2025). Data was retrieved directly from official state testing reports published on the Louisiana Department of Education portal.
  • South Carolina Department of Education: SC READY Assessment Results (2021–2025). Data was retrieved from public district-level and statewide assessment files made available by the South Carolina Department of Education.

Software & Package Citations

R (Base System)

R Core Team (2026). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

Package: tidyverse

Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. doi:10.21105/joss.01686 https://doi.org/10.21105/joss.01686.

Package: dplyr

Wickham H, François R, Henry L, Müller K, Vaughan D (2026). dplyr: A Grammar of Data Manipulation. R package version 1.2.1, https://dplyr.tidyverse.org.

Package: readr

Wickham H, Hester J, Bryan J (2026). readr: Read Rectangular Text Data. R package version 2.2.0, https://readr.tidyverse.org.

Package: parsnip

Kuhn M, Vaughan D (2026). parsnip: A Common API to Modeling and Analysis Functions. R package version 1.6.0, https://github.com/tidymodels/parsnip.

Package: broom

Robinson D, Hayes A, Couch S, Hvitfeldt E (2026). broom: Convert Statistical Objects into Tidy Tibbles. R package version 1.0.13, https://broom.tidymodels.org/.

Package: gt

Iannone R, Cheng J, Schloerke B, Haughton S, Hughes E, Lauer A, François R, Seo J, Brevoort K, Roy O (2026). gt: Easily Create Presentation-Ready Display Tables. R package version 1.3.0, https://gt.rstudio.com.

Package: marginaleffects

Arel-Bundock V, Greifer N, Heiss A (2024). “How to Interpret Statistical Models Using marginaleffects for R and Python.” Journal of Statistical Software, 111(9), 1-32. doi:10.18637/jss.v111.i09 https://doi.org/10.18637/jss.v111.i09.

Package: ggplot2

Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.