stimulus.plot() for stimulus plots in
matched/treated-stimulus designs (means and effects plots with null
resampling).stimulus.beeswarm() for compared-stimulus
designs.clear_stimulus_cache() to reset resampling cache
used by stimulus plotting functions.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().lm2() and print.lm2(): the
notes argument is deprecated (ignored). Passing
notes = TRUE or notes = FALSE emits a message
directing users to lm2_notes().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_labelsvar_labels() to get/set these labels for vectors
and data frames. This avoids depending on labelledplot_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.interprobe() for probing interactions: simple
slopes and Johnson–Neyman style marginal-effect curves for
x × z, using GAM or linear models.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.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.desc_var() evaluates calls such as df$x
correctly when data is not supplied, instead of mistakenly
using a same-named object from the search path.text2() applies vector arguments passed in
... (e.g. col) per label, fixing wrong colors
when labels differ (notably for plot_means() value
labels).plot_cdf() restores only selected graphics parameters
on exit (mar, mgp) so layouts using
par(mfrow = ...) are not reset. Similar graphics-state
cleanup was applied in other plotting functions where appropriate.plot_freq(), plot_density(), and
plot_cdf(): optional comparison of two vectors (in addition
to formula syntax); legend placed higher on the plot.table2(): clearer dimension labels for expressions such
as df$var > 10; very long labels are truncated.
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