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:Anne Corrine Huggins-Manley [aut], Anthony William Raborn [aut, cre]

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-4.5-any)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

Datasets:

On CRAN:

Conda:

2.70 score 1 scripts 712 downloads 5 exports 11 dependencies

Last updated 2 years agofrom:59817d9229. Checks:6 OK, 3 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 04 2025
R-4.5-winNOTEMar 04 2025
R-4.5-macNOTEMar 04 2025
R-4.5-linuxNOTEMar 04 2025
R-4.4-winOKMar 04 2025
R-4.4-macOKMar 04 2025
R-4.4-linuxOKMar 04 2025
R-4.3-winOKMar 04 2025
R-4.3-macOKMar 04 2025

Exports:estimate_impactnull_repsdplot_repsdrepsdrepsd_pval

Dependencies:clicrayongluehmslifecyclepkgconfigprettyunitsprogressR6rlangvctrs