transDIF 0.1.0
- 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()).