Changes in version 3.1.0 (2026-03-27)                  

Major changes

  - Archived timeROC dependency: The timeROC package (v0.4) is being
    archived on CRAN. Its required functions have been integrated
    directly into CalibrationCurves (R/timeROC_archived.R) with proper
    attribution. timeROC has been removed from Imports; pec has been
    added instead (required for ipcw()).

Bug fixes

  - valProbCluster(): cl.level parameter was ignored (Issue #22): The
    confidence level was hardcoded to 0.95 throughout the clustering
    pipeline. cl.level is now correctly passed to CGC(), MAC2(), and
    MIXC() and propagated to metaprop(), metagen(), and rma.mv() calls.
    Hardcoded "95%" plot labels have been replaced with dynamic labels
    via the new ci_pi_labels() helper function.

  - valProbSurvival(): crash near max follow-up (Issue #24): Uno's
    time-dependent AUC was evaluated at max(fit$y) - 0.01 instead of the
    user-specified timeHorizon, causing "incorrect number of dimensions"
    errors when the risk set was depleted. Fixed to use times =
    timeHorizon.

Enhancements

  - New "default" approach in valProbCluster(): Combines MAC2 (splines)
    for the overall calibration curve, confidence intervals, and
    prediction intervals, with MIXC for cluster-specific curves. This is
    now the default when approach is not specified. The returned object
    contains both the MAC2 overall results (results$overall) and the
    MIXC cluster results (results$clusters).

  - Unified the legend title to "Heterogeneity" across all
    valProbCluster() approaches.

  - Updated plot font to sans-serif and increased base size to 11 for
    improved readability across MIXC, MAC2, and CGC approaches.

Minor changes

  - Added input validation for cl.level in valProbCluster().
  - New helper function ci_pi_labels() for formatting
    confidence/prediction interval labels dynamically.
  - Added documentation of the "default" approach to the package
    vignette.

                 Changes in version 3.0.0 (2025-12-09)                  

  - Added valProbCluster() for calibration of clustered data with three
    approaches: MIXC, MAC2, and CGC.
  - Added valProbSurvival() for calibration of survival/time-to-event
    data.
  - Added genCalCurve() for generalized calibration across the
    exponential family.