NEWS
transDIF 0.1.0.9000
- New
td_sensitivity(): how comparability conclusions depend on the linking
assumption. Reports the ability difference, number of flagged items and
pass-rate impact under mode, purified and all-item linking; a parametric
bootstrap of the mode's stability; the items whose DIF verdict depends on
the linking; and an overall robust/sensitive verdict. Motivated by the
First International Mathematics Study illustration, where pervasive DIF on
a short test left the linking unidentified.
td_report() gains a sensitivity argument that adds this analysis to the
comparability report.
td_dif() gains c_fixed and c_se_fixed to fit the DIF model under an
analyst-chosen linking.
transDIF 0.1.0 (2026-10-08)
- Initial release.
- Per-group Rasch calibration with relative standard errors (
td_calibrate()).
- Robust linking by the precision-weighted mode of item differences, with a sandwich SE and a warning when two item clusters are equally plausible, and small-sample DIF detection with an empirical-Bayes spike-and-slab model and local false discovery rates (
td_dif()), plus a Mantel-Haenszel baseline (td_mh()).
td_features() drops item features with no variation (with a warning) instead of failing.
- Aggregate pass-rate impact with linking and DIF uncertainty (
td_impact()).
- Item-feature meta-regression and a draft comparability report (
td_features(), td_report()).