Changes in version 1.0.1 (2026-09-12)                  

CRAN Compliance

  - Restored the rstantools automatic configuration: removed the
    Config/ForceChoice/skip-rstantools-config field from DESCRIPTION,
    restored the standard configure and configure.win scripts, and
    regenerated the Stan export sources.

                 Changes in version 1.0.0 (2026-07-30)                  

New Features

Eight Model Families

  - fit.MIRT() - Multidimensional Item Response Theory (1PL--4PL) for
    binary dominance data, with optional Q-matrix structure.
  - fit.MGPCM() - Multidimensional Generalized Partial Credit Model for
    polytomous ordered-category responses.
  - fit.MGGUM() - Multidimensional Generalized Graded Unfolding Model
    for ideal-point polytomous responses with signed Q-matrix.
  - fit.FCMIRT() - Forced-Choice MIRT with item-level dominance
    endorsement and Luce--Plackett block-level ranking (RANK, MOLE,
    PICK).
  - fit.FCGGUM() - Forced-Choice GGUM with item-level ideal-point
    endorsement and block-level ranking.
  - fit.TIRT() - Thurstonian IRT for forced-choice with pairwise probit
    comparisons and latent utility differences.
  - fit.FCDCM() - Forced-Choice Diagnostic Classification Model with
    higher-order latent trait, DINA/DINO condensation rules, and exact
    attribute-profile marginalization.
  - fit.FCGDINA() - Forced-Choice GDINA model with DINA, DINO, ACDM, and
    GDINA item-level structures for ranking, most-least, and pick
    responses.

Estimation Backends

  - Stan (method = "stan"): Full Bayesian inference via Hamiltonian
    Monte Carlo (NUTS/HMC) with rstan.
  - iStEM (method = "iStEM"): Fast iterative Stochastic EM with
    Metropolis-within-Gibbs person sampling and L-BFGS-B item
    optimization.
  - EM (method = "EM"): Deterministic posterior-weight EM for FCGDINA.

Comprehensive Goodness-of-Fit

  - Limited-information M2 statistic (Maydeu-Olivares & Joe, 2005, 2006)
  - RMSEA with confidence intervals, SRMSR, RMSR
  - Comparative fit: CFI, TLI, IFI
  - Information criteria: AIC, AICc, BIC, CAIC, SABIC, HQIC
  - Pseudo-R2 measures: McFadden, Cox--Snell, Nagelkerke, and more
  - Local dependence: Yen's Q3 (raw and adjusted)
  - Posterior diagnostics: entropy, classification accuracy

Data Simulation

  - sim.data.MIRT(), sim.data.MGPCM(), sim.data.MGGUM() for traditional
    item response data.
  - sim.data.FCMIRT(), sim.data.FCGGUM(), sim.data.TIRT(),
    sim.data.FCDCM(), sim.data.FCGDINA() for forced-choice data.
  - All simulators support controlled parameter generation, factor
    correlation, and rotation.

Solution Rotation

  - rotate.MIRT() and rotate.matrix() for post-hoc rotation of MIRT
    solutions using promax or any GPArotation method.

S3 Methods

  - Consistent generics across all model classes: coef(), confint(),
    deviance(), fitted(), logLik(), nobs(), plot(), predict(), print(),
    residuals(), summary(), update(), vcov().

Bug Fixes

  - This is the initial CRAN release.

Notes

  - The package was previously developed under the name fcirt and has
    been substantially rewritten and expanded to support eight model
    families and the iStEM estimation backend.