Changes in version 1.0.1 (2026-05-21)                  

Fixed

  - Tests in test-cipma-comprehensive.R and test-fimix.R no longer reach
    into seminr's non-exported internals via
    seminr:::items_of_construct() and seminr:::all_endogenous(). They
    now use seminrExtras's own local helpers of the same name. This
    avoids breakage against forthcoming seminr 2.5.0, which refactors
    (and renames) those internal helpers.

                 Changes in version 1.0.0 (2026-04-29)                  

Major new features

  - Composite Overfit Analysis (COA): assess_coa(),
    predictive_deviance(), deviance_tree(), unstable_params(),
    group_rules(), competes() for diagnosing why and for whom PLS models
    fail to generalise out-of-sample.

  - Necessary Condition Analysis (NCA): assess_nca() with fully internal
    CE-FDH and CR-FDH algorithms (no external NCA package dependency).

  - NCA-ESSE: assess_nca_esse() implements the effect size sensitivity
    extension (Becker et al., 2026).

  - Combined Importance-Performance Map Analysis (cIPMA): assess_cipma()
    integrates IPMA with NCA to classify constructs into actionable
    priority quadrants. assess_ipma() provides an IPMA-only convenience
    wrapper. Supports HOC, mediation, and moderation models.

  - FIMIX-PLS: assess_fimix() and assess_fimix_compare() for EM-based
    latent class segmentation with multi-start initialisation and
    information criteria comparison.

  - PLS-POS: assess_pos(), assess_pos_compare(), and pos_segments() for
    prediction-oriented segmentation that maximises the sum of R-squared
    across segments (Becker et al., 2013).

  - CTA-PLS: assess_cta() for confirmatory tetrad analysis with
    automatic indicator borrowing for constructs with fewer than 4
    indicators (Gudergan et al., 2008).

  - Predictive Contribution of the Mediator (PCM): assess_pcm()
    evaluates whether a mediating construct improves out-of-sample
    prediction by comparing DA and EA approaches on isolated sub-models
    (Danks, 2021).

Improvements

  - assess_cvpat() and assess_cvpat_compare(): fixed bootstrap test
    branches, loss function return types, and reference metadata.

  - congruence_test(): fixed division guard, upper-triangular masking,
    and bootstrap robustness for nboot = 0.

  - All features include print(), summary(), and plot() S3 methods.

  - Comprehensive test suite (740+ tests).

  - Demo files for all features: demo("seminr-pls-<feature>").

  - Updated vignette with examples for all features.

Dependencies

  - Requires seminr >= 2.4.0.
  - rpart added to Imports (for COA deviance trees).
  - MASS, paran, psych, learnr added to Suggests.

                 Changes in version 0.9.0 (2026-01-29)                  

  - Initial CRAN release with CVPAT and congruence testing.