Changes in version 0.3.0 (2026-05-20)                  

New functions

  - Added stimulus.plot() for stimulus plots in matched/treated-stimulus
    designs (means and effects plots with null resampling).
  - Added stimulus.beeswarm() for compared-stimulus designs.
  - Added clear_stimulus_cache() to reset resampling cache used by
    stimulus plotting functions.

Improvements

  - t.test2(): now reports Cohen's d for two-sample independent tests
    (returned as d and printed after sample sizes).
  - t.test2(): missing-value note no longer double-counts rows where the
    grouping variable is NA.
  - lm2(): explanatory notes are no longer printed with the regression
    table; they are stored when the model is printed and shown via the
    new lm2_notes() function. The print output ends with a reminder to
    run lm2_notes().

Deprecated

  - lm2() and print.lm2(): the notes argument is deprecated (ignored).
    Passing notes = TRUE or notes = FALSE emits a message directing
    users to lm2_notes().

                 Changes in version 0.2.1 (2026-04-25)                  

changes to pass CRAN inspection

  - plot_means(): removed the save.as argument (no longer saves plots to
    PNG/SVG).
  - t.test2(): documented S3 registration as t.test2 for base::t to
    avoid recurring CRAN S3 consistency notes while keeping direct
    t.test2(...) usage unchanged.
  - desc_var(): removed dependency on labelled; now relies on new
    function var_labels

New function

  - Added var_labels() to get/set these labels for vectors and data
    frames. This avoids depending on labelled

                        Changes in version 0.2.0                        

New functions

  - Added plot_means() for barplots of group means with confidence
    intervals, optional comparisons and interaction-style contrasts, up
    to three grouping variables in the formula, optional clustered
    standard errors, and saving to PNG or SVG.
  - Added interprobe() for probing interactions: simple slopes and
    Johnson–Neyman style marginal-effect curves for x × z, using GAM or
    linear models.

Improvements

  - plot_freq(): improved behavior when there are many distinct values;
    grouped plots support up to four levels of the grouping variable.
  - lm2(): mean column shows percentages for factor levels and
    factor×factor interactions as intended; baseline factor level row
    shows the percentage of observations like other levels.
  - desc_var(): when the response variable is missing, only the intended
    error is shown (no spurious “restarting interrupted promise
    evaluation” warning).
  - scatter.gam(): supports direct coordinates and formula syntax
    (including df$y ~ df$x); axis labels use short variable names for $
    formulas; ylim and other ... arguments no longer conflict with
    internal plot arguments; small vertical buffer on the lower
    frequency panel.
  - Messages that used red4 now use red2 for readability in dark
    terminals (including messages from plot_freq(), plot_density(),
    plot_cdf(), clear(), twolines(), and exit()).
  - t.test2() performance improvements.

Bug fixes

  - desc_var() evaluates calls such as df$x correctly when data is not
    supplied, instead of mistakenly using a same-named object from the
    search path.
  - text2() applies vector arguments passed in ... (e.g. col) per label,
    fixing wrong colors when labels differ (notably for plot_means()
    value labels).
  - plot_cdf() restores only selected graphics parameters on exit (mar,
    mgp) so layouts using par(mfrow = ...) are not reset. Similar
    graphics-state cleanup was applied in other plotting functions where
    appropriate.

                 Changes in version 0.1.9 (2026-02-26)                  

  - plot_freq(), plot_density(), and plot_cdf(): optional comparison of
    two vectors (in addition to formula syntax); legend placed higher on
    the plot.
  - table2(): clearer dimension labels for expressions such as df$var
    > 10; very long labels are truncated.