Changes in version 0.1.4                        

  - Added a symbol argument to all plot.*() methods, allowing
    study-level markers to be drawn as rectangles, ellipses, diamonds,
    triangles, crosses, plus signs, or stars.

  - Subgroup plots now distinguish subgroups by point symbol as well as
    colour by default. The previous appearance, using rectangles for all
    subgroups, can be reproduced by setting symbol = "rectangle".

  - Added the size = "sampsize_revman" and size = "se_revman" options,
    following RevMan-style symbol-sizing conventions, to support visual
    consistency with as_revman() exports. The analogous size =
    "eb_revman" option is available for latent-class models.

  - Corrected a bug in plot.Reitsma() with the default size = "fisher".
    The covariance used to construct the matrix G for the SROC plot is
    now calculated correctly.

  - Added the size = "fisher" option to plot.RutterGatsonis(),
    plot.RutterGatsonisSubgroup(), and plot.ReitsmaSubgroup(). It is now
    the default in plot.RutterGatsonis().

  - Added fitReitsmaTMB() and fitReitsmaSubgroupTMB(), which use custom
    TMB templates rather than glmmTMB and may provide improved numerical
    robustness in difficult or near-boundary cases.

  - Corrected a bug in the plot() and as_revman() methods for
    ReitsmaSubgroup models when sensitivity and/or specificity are
    constrained to be common across subgroups.

  - Added optional study-level confidence intervals (studyCI = TRUE) and
    study labels (studylabels = TRUE) to SROC plotting methods.

  - Improved starting-value initialization across model families.
    Robust, finite fallback values are now used when preliminary model
    fits or empirical estimates are unavailable, including for sparse
    and degenerate datasets.

  - Revised the likelihood-ratio-test examples and documentation to
    caution against using the ordinary chi-squared reference
    distribution when a reduced model constrains one or more
    random-effects variances to zero. The corresponding zero-variance
    boundary comparison was removed from the vignette.

  - Fixed manual-page titles to use title case consistently.

                 Changes in version 0.1.3 (2026-09-26)                  

  - summary() methods now return objects of dedicated S3 classes
    ("summary.DTAmodel" and model-specific subclasses) rather than plain
    lists, with a corresponding print.summary.DTAmodel() method.

  - Refactored forest-plot construction across model classes into shared
    internal helpers (getForestSensSpec(), getForestSensSpecLCA(), and
    getForestPlot()) to reduce code duplication.

  - coef() and vcov() methods are now available for all model classes.
    Examples were updated to use summary() and these accessors rather
    than accessing internal list components directly.

                 Changes in version 0.1.2 (2026-08-26)                  

  - Maintenance release.

                 Changes in version 0.1.1 (2026-07-26)                  

  - Added latent-class models.

                 Changes in version 0.1.0 (2026-07-16)                  

  - Initial CRAN release.