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Changelog

Source: NEWS.md

erplots 0.2.0

CRAN release: 2026-10-04

New features

  • Added er_tte(), a third mini-grammar (alongside er_plot()/er_vpc()) for Kaplan-Meier/survival-over-time figures, built around a time axis, a survival-probability axis, and an optional discrete stratify_by. Five singleton layers: er_tte_add_curve() (the KM step curve + confidence band), er_tte_add_censor() (censoring tick marks), er_tte_add_risktable() (a number-at-risk panel stacked below the curve), er_tte_add_summary() (a corner-placed text/label annotation – a log-rank test by default, or subject/event counts or a fitted model’s coefficients/goodness-of-fit via style), and er_tte_add_model() (a fitted parametric S(t) curve/ribbon overlay). er_tte_theme() styles labels, titles, axis limits, formatters, the legend key, and panel heights, mirroring er_plot_theme()/er_vpc_theme(). See the new plot-tte vignette.
  • Added er_predict_survival(), a fourth model-interface generic (see ?er_model_interface) powering er_tte_add_model()’s S(t) overlay. The new companion package ertte (GitHub-only, like erglm/ emaxnls, but not a declared Suggests/Remotes dependency of erplots) implements it, alongside the existing er_predict()/ er_simulate()/er_summary() methods.
  • cut_quantile()/cut_exposure_quantile() gain a ties argument controlling how a value that sits exactly on an interior quantile break is assigned ("upward", the default and prior behaviour; "downward"; or "split-even", which randomly balances tied values between the two candidate bins), plus an opt-in seed argument for reproducing "split-even"’s random tie-break. The resolved rule is recorded as a "ties" attribute on the returned factor.
  • cut_quantile()/cut_exposure_quantile() gain a quantile_type argument, passed straight through to [stats::quantile()]’s own type argument for computing the quantile break points. Defaults to 7 (unchanged prior behaviour) and is recorded as a "quantile_type" attribute on the returned factor.
  • cut_quantile()/cut_exposure_quantile() gain a labeller argument for customising quantile-bin labels: a function called as labeller(n, breaks), or a character vector used directly. Defaults to NULL (unchanged "Q1"/"Q2"/… labelling); cut_exposure_quantile()’s separate "Placebo" level is untouched by labeller.
  • er_plot_add_quantiles()/er_plot_add_groups() gain ties/ quantile_type/labeller arguments, forwarded to cut_exposure_quantile()/cut_quantile(). These are local to each call – they aren’t required to agree across different er_plot_add_groups() calls, or with er_plot_add_quantiles() – except in one case: er_plot_build() now warns if er_plot_add_groups() bins the exposure variable itself differently than er_plot_add_quantiles() does, since the two panels would then show inconsistent quantile bins for the same variable.
  • er_vpc() gains ties/quantile_type/labeller for plot_by, plus a seed argument for reproducing a "split-even" tie-break. Unlike the er_plot_add_quantiles()/er_plot_add_groups() arguments above, these live on er_vpc() itself rather than on er_vpc_add_observed()/er_vpc_add_simulated(), since the observed and simulated layers must always bin plot_by identically – er_vpc_add_simulated()’s own seed argument now also seeds its independent "split-even" tie-break.
  • er_vpc() gains an optional stratify_by for faceting a VPC into one panel per discrete stratum, mirroring er_plot()’s own stratification (facet-only here, since a VPC has no colour/fill precedence rule to reconcile). Errors if stratify_by resolves to the same variable as plot_by.
  • er_style_tag() gains a label argument for registering a builder under a short string (e.g. label = "logrank"), so the corresponding _add_*() function’s style argument can be given that string instead of the function itself (e.g. er_plot_add_model(mod, style = "spaghetti") in place of style = er_style_model_spaghetti). Every built-in builder across all three grammars is tagged with one; see er_style_labels() to list what’s registered (optionally filtered to one layer), and ?er_style_tag for the full naming/lookup contract. label requires layer to also be set in the same call, since the registry is keyed by (layer, label), not label alone. A new overwrite argument (default FALSE) controls what happens when re-registering a (layer, label) pair already assigned to a different function: errors by default; overwrite = TRUE replaces it unconditionally. Re-registering the identical function is always a silent no-op regardless of overwrite.

Improvements

Breaking changes

  • er_style_tag()’s zorder argument is renamed to draw_order (same "foreground"/"background" values); a builder tagged with the old name needs updating (e.g. er_style_tag(fn, draw_order = "background") in place of zorder = "background")). layout is split into two independent arguments: layout keeps its existing "overlay"/ "panel" meaning for a data-layer builder, while a VPC observed/ simulated builder’s "categorical"/"continuous" distinction moves to a new vpc_layout argument – the two had shared one argument and attribute despite meaning unrelated things. See ?er_style_tag.
  • er_style_tag()’s layer values are renamed to be grammar-prefixed: "model"/"summary"/"quantile"/"data"/"group" (er_plot()) become "plot_model"/"plot_summary"/"plot_quantile"/"plot_data"/ "plot_group"; "observed"/"simulated" (er_vpc()) become "vpc_observed"/"vpc_simulated"; "curve"/"censor"/"risktable" (er_tte()) become "tte_curve"/"tte_censor"/"tte_risktable". "tte_model"/"tte_summary" are unchanged (already grammar-prefixed). A custom builder tagged with one of the old values needs updating; see ?er_style_tag.
  • stratify_by must now name a discrete/categorical variable in er_vpc(); a numeric column errors instead of being automatically split into quantile bins, and the n_strata argument is removed. Bin a continuous covariate yourself first with cut_quantile()/ cut_exposure_quantile(), which also gives full control over bin count, tie-breaking, and labels – see ?er_vpc. (er_tte()’s own stratify_by has the same discrete-only requirement from the outset, being new in this release.)
  • style/keep_strata’s argument position is standardised across every er_plot_add_*()/er_vpc_add_*()/er_tte_add_*() layer function: style now always comes immediately after object and any required model/grouping argument, and keep_strata (where the layer has one) always comes immediately after style. conf_level (where the layer has one) always comes immediately after keep_strata, ahead of any layer-specific argument such as er_plot_add_quantiles()’s bins or er_tte_add_model()’s time_grid. Calls that name these arguments (the documented usage) are unaffected; positional calls that relied on the previous ordering will need updating.
  • er_vpc()’s stratify_by argument moves to immediately after response, matching where er_plot()/er_tte() already place their own stratify_by; it previously sat after plot_by’s binning arguments (plot_by/n_bins/ties/quantile_type/labeller). Calls that name stratify_by (the documented usage) are unaffected.
  • The position of ... relative to a builder’s own named arguments is standardised to always come last, across every built-in er_style_*() builder: er_style_model_ribbonline()/_line()/ _spaghetti(), er_style_data_overlay()/_boxjitter()/_hex(), er_style_tte_curve_km(), er_style_tte_censor_ticks(), er_style_tte_risktable_text(), er_style_tte_model_line(), and er_style_tte_summary_logrank() previously placed ... immediately after theme, ahead of their own style-specific arguments, unlike every other built-in builder. Calls that name these arguments (the documented usage) are unaffected.
  • The “number of quantile bins” argument is renamed to n_bins everywhere, matching er_vpc()’s existing name: bins in er_plot_add_quantiles()/er_plot_add_groups(), and n in cut_quantile()/cut_exposure_quantile(), all become n_bins. A custom labeller function is now called as labeller(n_bins, breaks) rather than labeller(n, breaks) – since this call is positional, only the documentation changed; existing custom labeller functions keep working regardless of their own parameter names. er_style_data_hex()’s and er_style_group_histogram()’s own bins arguments (2D-hexbin/histogram bin counts, forwarded straight to the matching ggplot2 geom) are unrelated and unchanged.
  • er_style_data_overlay()’s and er_style_tte_censor_ticks()’s size argument (a plotted point’s size) is renamed to point_size, matching the quantile/VPC builder family’s existing name for the same concept (er_style_quantile_errorbar(), er_style_vpc_observed/ simulated_mean_errorbar(), etc.) and the package’s own <thing>_size convention (label_size, text_size, jitter_size).
  • er_style_group_linerange()’s size argument is renamed to scale_factor, since it isn’t a point size at all – it’s a single multiplier applied to three different elements (a dot and two line ranges) at three different ratios, so neither size nor point_size described it accurately.
  • er_style_group_linerange()’s alpha_dot/alpha_inner/alpha_outer are renamed to dot_alpha/inner_alpha/outer_alpha, matching the <thing>_alpha suffix order used by every other alpha argument in the package (ribbon_alpha, box_alpha, jitter_alpha).

Bug fixes

  • er_plot_add_model()’s curve/ribbon no longer goes stale after er_plot_theme(xlim = ...) narrows or widens the exposure axis once the model layer has already been added – the prediction grid is now recomputed at build time rather than cached from add-layer time (#14).
  • The data, quantile, and group layers now drop (and warn about) any observations falling outside er_plot_theme(xlim = )/ylim = ), instead of silently handing them to a geom that renders past the visible panel with no visual cue (#16).
  • er_vpc_add_observed()/er_vpc_add_simulated() summary markers falling outside er_vpc_theme(xlim = )/ylim = ) are now dropped, with a warning, instead of silently drawn past the panel (#17).
  • er_plot() now errors clearly when stratify_by names a numeric column, instead of silently mapping it to a continuous colour scale (which broke every stratified builder’s discrete-groups assumption – ribbons, per-stratum lines, dodging – with no warning). stratify_by has always been documented as requiring a discrete variable; this was simply never validated.
  • er_plot_add_groups()’s bins argument now actually controls the number of quantile bins used for a continuous grouping variable. Previously documented but silently ignored – every continuous grouping variable was always split into cut_quantile()/cut_exposure_quantile()’s own default of 4 bins, regardless of what bins was set to.
  • er_style_quantile_errorbar_vlines()/er_style_quantile_pointrange_vlines()’s bin-boundary lines/labels are now dropped (and warn), like every other layer’s out-of-range markers, when they fall outside er_plot_theme(xlim = ), instead of silently landing off the visible panel with no cue (#16).

Documentation

erplots 0.1.2

CRAN release: 2026-09-09

Addresses CRAN reviewer feedback on the 0.1.1 submission. User-facing changes:

  • er_plot_add_data()’s two jittered builders (er_style_data_overlay(), er_style_data_boxjitter()) no longer hard-code a specific RNG seed (previously a literal 1234L in R/er-plot-layer.R, used so that repeated plot() calls on the same object always showed identical jitter). Seeding is now opt-in only: pass seed = <value> through er_plot_add_data()’s own ... for reproducible jitter across rebuilds of the same object; with no seed (the default), jitter draws from the ambient RNG stream and differs from one build to the next, like any other jittered geom.
  • er_plot_add_groups()’s jittered builders (er_style_group_boxjitter(), er_style_group_violinjitter()) gain the same opt-in seed support, for consistency – their jitter previously had no seed control at all. withr moves from Suggests to Imports to support this.

erplots 0.1.1

  • No user-facing changes. Fixes a documentation issue flagged by CRAN’s Debian pretest check.

erplots 0.1.0

Initial CRAN submission.

er_plot(): the plotting mini-language

  • er_plot() builds a fluent, pipe-based specification for exposure-response plots, generalised across binary, continuous, and count responses (response_type = c("auto", "binary", "continuous", "count"), auto-detected when not supplied).
  • Six pipeline verbs attach layers to the specification – nothing is drawn until er_plot_build()/print()/plot() – and pipe order never affects the built plot:
    • er_plot_add_model() – a model curve/ribbon.
    • er_plot_add_summary() – a corner-placed text/label annotation (a model-derived statistic, or a plain observation count).
    • er_plot_add_quantiles() – a quantile-binned response-rate/mean summary with confidence interval.
    • er_plot_add_data() – a raw-data layer, either an overlay drawn on the main panel or one or more panels stacked below it.
    • er_plot_add_groups() – stacked panels showing the exposure distribution per group variable (the one additive, non-singleton layer).
  • stratify_by splits colour/facet encoding across strata, following a documented colour/facet precedence rule (see vignettes/articles/design.Rmd).
  • er_plot_theme() styles labels, titles, axis limits, discrete/ continuous colour and fill palettes, formatters, the legend key glyph, and relative panel heights, without changing which variable drives which aesthetic.

The model interface

  • Any model implementing er_predict() can be visualised; additionally implementing er_simulate() and/or er_summary() enables uncertainty spaghetti plots/VPCs and model-derived summary annotations. See ?er_model_interface.
  • erplots never fits a model itself – it is designed to work alongside companion packages that implement the interface, such as erglm (GLM-based exposure-response models) and emaxnls (Emax/sigmoidal dose-response models).

The builder system

  • Every layer-adding function accepts a style argument (a er_style_*() builder function) that can be swapped for another built-in or a fully custom builder, with a documented interface (?er_style) and self-declared metadata via er_style_tag().
  • Built-in builders cover multiple visual idioms per layer, e.g. ribbon/line/spaghetti model curves, p-value/n/coefficients/ goodness-of-fit summaries, errorbar/pointrange quantile summaries (with boundary-labelled _vlines variants), overlay/hexbin/ boxjitter data layers, and boxplot/violin/histogram/boxjitter/ violinjitter group panels.

er_vpc(): the visual predictive check mini-grammar

  • er_vpc() |> er_vpc_add_observed() |> er_vpc_add_simulated() mirrors er_plot()’s object/layer/builder architecture for building visual predictive checks, with an optional stratify_by for faceted panels.
  • Three visual idioms are available via style: an adaptive mean/ errorbar default, a continuous-x percentile-band idiom, and an adaptive quantile-errorbar idiom.
  • er_vpc_theme() styles labels, titles, axis limits, and formatters.

Bundled example dataset

  • erplots_data – 4,000 simulated subjects spanning three exposure measures and five response columns (continuous, binary, and count), built to exercise every response type and modelling scenario used in the package’s documentation and vignettes.