Package: achieveGap Type: Package Title: Modeling Achievement Gap Trajectories with Hierarchical Penalized Splines Version: 0.1.0 Authors@R: person("Subir", "Hait", email = "haitsubi@msu.edu", role = c("aut", "cre"), comment = c(ORCID = "0009-0004-9871-9677")) Description: Implements a hierarchical penalized spline framework for estimating achievement gap trajectories in longitudinal educational data. The achievement gap between two groups (e.g., low versus high socioeconomic status) is modeled directly as a smooth function of grade while the baseline trajectory is estimated simultaneously within a mixed-effects model. Smoothing parameters are selected using restricted maximum likelihood (REML), and simultaneous confidence bands with correct joint coverage are constructed using posterior simulation. The package also includes functions for simulation-based benchmarking, visualization of gap trajectories, and hypothesis testing for global and grade-specific differences. The modeling framework builds on penalized spline methods (Eilers and Marx, 1996, ) and generalized additive modeling approaches (Wood, 2017, ), with uncertainty quantification following Marra and Wood (2012, ). License: GPL (>= 3) Encoding: UTF-8 Roxygen: list(markdown = TRUE) RoxygenNote: 7.3.3 Depends: R (>= 4.1.0) Imports: mgcv (>= 1.9-0), lme4 (>= 1.1-0), MASS (>= 7.3-0), ggplot2 (>= 3.4.0) Suggests: knitr (>= 1.36), rmarkdown (>= 2.11), testthat (>= 3.0.0) VignetteBuilder: knitr Config/testthat/edition: 3 URL: https://github.com/causalfragility-lab/achieveGap BugReports: https://github.com/causalfragility-lab/achieveGap/issues Config/pak/sysreqs: cmake make Repository: https://causalfragility-lab.r-universe.dev Date/Publication: 2026-05-05 19:12:23 UTC RemoteUrl: https://github.com/causalfragility-lab/achievegap RemoteRef: HEAD RemoteSha: 026b8d2b50c7efe7ae5aa0d4dbdc0f143011d666 NeedsCompilation: no Packaged: 2026-07-13 05:16:04 UTC; root Author: Subir Hait [aut, cre] (ORCID: ) Maintainer: Subir Hait