Package: repsd 1.0.1
repsd: Root Expected Proportion Squared Difference for Detecting DIF
Root Expected Proportion Squared Difference (REPSD) is a nonparametric differential item functioning (DIF) method that (a) allows practitioners to explore for DIF related to small, fine-grained focal groups of examinees, and (b) compares the focal group directly to the composite group that will be used to develop the reported test score scale. Using your provided response matrix with a column that identifies focal group membership, this package provides the REPSD values, a simulated null distribution of possible REPSD values, and the simulated p-values identifying items possibly displaying DIF without requiring enormous sample sizes.
Authors:
repsd_1.0.1.tar.gz
repsd_1.0.1.zip(r-4.5)repsd_1.0.1.zip(r-4.4)repsd_1.0.1.zip(r-4.3)
repsd_1.0.1.tgz(r-4.4-any)repsd_1.0.1.tgz(r-4.3-any)
repsd_1.0.1.tar.gz(r-4.5-noble)repsd_1.0.1.tar.gz(r-4.4-noble)
repsd_1.0.1.tgz(r-4.4-emscripten)repsd_1.0.1.tgz(r-4.3-emscripten)
repsd.pdf |repsd.html✨
repsd/json (API)
NEWS
# Install 'repsd' in R: |
install.packages('repsd', repos = c('https://anthonyraborn.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/anthonyraborn/repsd/issues
- timmsData - Sample data from TIMMS
- timmsDiffic - Sample TIMMS item difficulties
- timmsDiscrim - Sample TIMMS item discriminations
Last updated 2 years agofrom:59817d9229. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-win | OK | Nov 04 2024 |
R-4.5-linux | OK | Nov 04 2024 |
R-4.4-win | OK | Nov 04 2024 |
R-4.4-mac | OK | Nov 04 2024 |
R-4.3-win | OK | Nov 04 2024 |
R-4.3-mac | OK | Nov 04 2024 |
Exports:estimate_impactnull_repsdplot_repsdrepsdrepsd_pval
Dependencies:clicrayongluehmslifecyclepkgconfigprettyunitsprogressR6rlangvctrs
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Estimate the effect size difference between focal and composite group abilities | estimate_impact |
null_repsd | null_repsd |
REPSD Null vs Observed Histogram | plot_repsd |
repsd | repsd |
Calculating p-values for repsd | repsd_pval |
Sample data from TIMMS | timmsData |
Sample TIMMS item difficulties | timmsDiffic |
Sample TIMMS item discriminations | timmsDiscrim |