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                      CHANGELOG irtlink
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irtlink 0.1.0 (2026-10-06)
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Initial release.

ADDED * Internal marginal maximum likelihood EM calibration
        (1PL, 2PL, 3PL): separate, concurrent (full or partial
        invariance, with chain, joint, and restricted joint
        compositions), fixed item parameter calibration (FIPC),
        and regularized calibration with a smooth Bayesian
        information criterion (SBIC).
ADDED * Polytomous items via the generalized partial credit
        model (GPCM) and the partial credit model (PCM) with
        separate calibration, chain and pairwise joint linking
        by every method, joint and pairwise Haberman linking,
        jackknife and approximate jackknife linking errors,
        EAP person scores, and a polytomous response simulator.
ADDED * Linking via link_groups() (chain, joint, restricted
        joint): mean-mean, mean-geometric mean, Haberman with
        robust Lq loss, Haebara, and Stocking-Lord, each joint
        method with a simultaneous and a pairwise variant, and a
        selectable reference group. The Haebara and Stocking-Lord
        criteria compare the full 3PL response functions when
        guessing parameters are present.
ADDED * Linking errors: (bias-corrected) delete-one item
        jackknife, approximate one-step jackknife, and sandwich
        estimators. A cluster argument deletes whole testlets
        instead of single items in the jackknife and the
        approximate jackknife.
ADDED * Item parameter covariances, including dependent_vcov()
        (stacked sandwich or person bootstrap) for dependent
        person samples.
ADDED * DIF diagnostics: root mean square deviation (RMSD)
        statistics and per-item likelihood-ratio tests, with
        iterative purification.
ADDED * Person scores (expected a posteriori (EAP) and weighted
        likelihood (WLE) estimates), a response data simulator
        (uniform and non-uniform DIF, dependent person samples),
        and a linking-design inspector.
ADDED * Person sampling weights (pweights, e.g. senate weights)
        in every calibration strategy.
NOTE  * No runtime dependencies beyond base R and Rcpp.