achieveGap
Modeling Achievement Gap Trajectories with Hierarchical Penalized Splines
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, <doi:10.1214/ss/1038425655>) and generalized additive modeling approaches (Wood, 2017, <doi:10.1201/9781315370279>), with uncertainty quantification following Marra and Wood (2012, <doi:10.1111/j.1467-9469.2011.00760.x>).
Downloads
474
Last 30 days
8719th
1.6K
Last 90 days
2K
Last year
Trend: -9% (30d vs prior 30d)
7
Last 30 days
28
Last 90 days
39
Last year
Trend: 0% (30d vs prior 30d)
12
Last 7 days
45
Last 30 days
1
All-time
autoCRAN-only: this name is served only by autoCRAN, so the count is exact.
CRAN Check Status
Show all 13 flavors
| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
Changelog
Full NEWS →v0.1.0
Initial release
• First public release of the achieveGap package.
• Implements hierarchical penalized spline models for estimating
achievement gap trajectories in longitudinal educational data.
• Provides the main function
gap_trajectory() for fitting jointmixed-effects spline models with REML smoothing selection.
• Includes simultaneous confidence bands based on posterior simulation.
• Supports visualization and summary methods for estimated gap trajectories.
• Includes simulation utilities for benchmarking model performance.
Check History
OK 5 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 19, 2026
Code
Structure
Lines of code
2,945
Files
35
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
7
Internal functions
4
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.11
testthat edition
3
CI present
No
CI type
[]
PR gated
No
Docs
Return-value doc rate
100%
\dontrun example ratio
66.7%
Roxygen coverage
100%
Has pkgdown
No
NEWS present
Yes
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
100%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.1.0
System requirements
–
C++ standard
–
License
GPL (>= 3)
License flags
SPDX valid, OSI approved
History
Versions
1
First release
2026-03-19
Latest release
2026-03-19
Avg cadence
–
Cold removal rate
–
Dep drift
0
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/cran-code-metrics.