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Simulated-layer builders for VPC plots

Source: R/er-vpc-style-simulated.R
er_style_vpc_simulated.Rd

Builder functions for the simulated layer (er_vpc_add_simulated()), drawing the simulated side of a visual predictive check as a mean + percentile interval per bin (the default, adaptive to plot_by's type), continuous-x percentile bands, or a point/interval per bin and per requested percentile.

Usage

er_style_vpc_simulated_quantile_ribbon(
  data,
  config,
  exposure,
  response,
  theme,
  ribbon_alpha = 0.3,
  ribbon_edges = FALSE,
  edge_linetype = "dotted",
  edge_linewidth = 0.5,
  edge_colour = "grey50",
  median_linetype = "dashed",
  median_linewidth = 0.5,
  median_colour = "grey30",
  ...
)

er_style_vpc_simulated_quantile_errorbar(
  data,
  config,
  exposure,
  response,
  theme,
  point_size = 1.5,
  errorbar_width = NULL,
  dodge = 0,
  prob_dodge_width = 0,
  ...
)

er_style_vpc_simulated_mean_errorbar(
  data,
  config,
  exposure,
  response,
  theme,
  point_size = 2,
  errorbar_width = NULL,
  dodge = 0,
  show_label = FALSE,
  label_size = 3,
  ...
)

Arguments

data

The original data frame.

config

Configuration for the simulated layer.

exposure

Exposure variable.

response

Response variable.

theme

Theme components.

ribbon_alpha

Fill transparency for er_style_vpc_simulated_quantile_ribbon()'s bands. Defaults to 0.3.

ribbon_edges

Whether er_style_vpc_simulated_quantile_ribbon() additionally draws a line along each band's own ci_lower/ci_upper bounds, on top of the shaded ribbon fill – mirrors er_style_model_ribbonline()'s own ribbon_edges argument. Default FALSE (ribbon fill only). Useful when several requested percentiles' bands overlap: the edge lines stay legible even where the fills merge into an indistinguishable blob.

edge_linetype, edge_linewidth, edge_colour

Styling for er_style_vpc_simulated_quantile_ribbon()'s optional edge lines (only drawn when ribbon_edges = TRUE). Defaults to a thin, light dotted line ("dotted", 0.5, "grey50") that stays unobtrusive even when several bands' edges overlap.

median_linetype, median_linewidth, median_colour

Styling for er_style_vpc_simulated_quantile_ribbon()'s median line, drawn at each band's y_mid. Defaults match the previous fixed styling ("dashed", 0.5, "grey30").

...

Additional named arguments forwarded from er_vpc_add_simulated()'s own ....

point_size

Point size for both point/interval builders. Defaults to 1.5 for er_style_vpc_simulated_quantile_errorbar(), or 2 for er_style_vpc_simulated_mean_errorbar().

errorbar_width

Width of er_style_vpc_simulated_mean_errorbar()'s and er_style_vpc_simulated_quantile_errorbar()'s error bars. Interpreted differently depending on plot_by's type: for a categorical plot_by, it's a bar width in the same implied unit-scaled category-gap units ggplot2::geom_errorbar() normally expects; for a numeric plot_by, it's a fraction of plot_by's own range (config$group_limits), so 1 would span the full range. Defaults to NULL, which resolves to 0.15 (er_style_vpc_simulated_quantile_errorbar()) or 0.2 (er_style_vpc_simulated_mean_errorbar()) for a categorical plot_by, or 0.025 for a numeric one.

dodge

Horizontal offset (as a fraction of plot_by's own range, like errorbar_width for a numeric plot_by) applied to all of this builder's error bars/points, for both er_style_vpc_simulated_mean_errorbar() and er_style_vpc_simulated_quantile_errorbar(). Default 0 (no offset, the previous behaviour); pair with an opposite-signed dodge on the corresponding observed builder to manually separate the two layers where they'd otherwise overlap at the same bin. See er_style_vpc_observed()'s own dodge docs for the full explanation, including the categorical-plot_by restriction.

prob_dodge_width

Horizontal spread (as a fraction of plot_by's own range) applied to er_style_vpc_simulated_quantile_errorbar()'s requested probs within a single bin. Default 0 (the previous behaviour); see er_style_vpc_observed()'s own prob_dodge_width docs.

show_label

For er_style_vpc_simulated_mean_errorbar() only: whether to draw config$summary's y_mid_lbl (the mean, formatted via er_vpc_theme()'s format_percent/format_number) as a text label just above each point's upper CI bound. Default FALSE (no label, the previous behaviour); see er_style_vpc_observed()'s own show_label docs.

label_size

Text size for show_label's label. Defaults to 3.

Value

A list of geoms; see er_style().

Details

See er_style_vpc() for the shared interface every VPC-grammar builder implements.

Choosing a builder

All three builders plot the simulated side of a bin against the observed side drawn by their er_style_vpc_observed() counterpart; which one to reach for depends on how much of the response's distribution you need to see, and what kind of response/plot_by you have:

  • er_style_vpc_simulated_mean_errorbar() (the default) – one point + percentile interval per bin, summarising the mean only. Works for every response type and either kind of plot_by. Start here unless you specifically need percentile bands.

  • er_style_vpc_simulated_quantile_ribbon() – a shaded band per requested percentile, for a fuller picture of the response's distribution across bins. Requires a continuous/count response and a numeric plot_by; pairs with er_style_vpc_observed_quantile_line().

  • er_style_vpc_simulated_quantile_errorbar() – a point + interval per requested percentile per bin, the discrete-bin analogue of the ribbon idiom above. Same response-type restriction, but also works with a categorical plot_by; pairs with er_style_vpc_observed_quantile_errorbar().

Mean/errorbar (default)

er_style_vpc_simulated_mean_errorbar() plots config$summary's mean + percentile interval (of the mean, across replicates), adapting its x-position to plot_by's type (config$is_numeric_group): equally spaced at each bin's categorical (or quantile-bin) label when plot_by is categorical, or at each bin's numeric median (x_median, from config$summary) on the plot_by's own numeric scale when plot_by is numeric. Because it adapts its x-position family at build time rather than declaring one statically, it carries no vpc_layout tag – pair it with er_style_vpc_observed_mean_errorbar(), which mirrors the same adaptive logic.

Percentile ribbon

er_style_vpc_simulated_quantile_ribbon() plots config$percentiles – one shaded band (median line + interval) per requested percentile – at each bin's numeric midpoint on plot_by's own numeric scale, for pairing with er_style_vpc_observed_quantile_line(). config$percentiles is only computed for a continuous/count response (see er_vpc()'s probs argument); calling er_style_vpc_simulated_quantile_ribbon() without it errors.

Percentile errorbar

er_style_vpc_simulated_quantile_errorbar() plots config$percentiles – a point + across-replicate percentile interval for each requested percentile – for pairing with er_style_vpc_observed_quantile_errorbar(). Like that builder (and like er_style_vpc_simulated_mean_errorbar()), it adapts its x-position to plot_by's type, carries no vpc_layout tag, supports both a numeric and a categorical plot_by, and requires a continuous/count response, erroring informatively without config$percentiles. As with the observed-layer counterpart, when more than one percentile is requested they are currently all plotted at the same x-position within a bin rather than dodged apart.

Legends and overlap

er_style_vpc_simulated_mean_errorbar()/er_style_vpc_simulated_quantile_errorbar() map a constant color = "Simulated"; er_style_vpc_simulated_quantile_ribbon() maps a constant fill = "Simulated". ggplot2 merges either into the paired observed builder's own "Observed" legend entry (same aesthetic) into one combined legend; the ribbon's fill legend is separate from the point/errorbar builders' color legend.

When several requested percentiles' bands sit close together (small per-bin samples, few simulated replicates, or probs values close to one another), er_style_vpc_simulated_quantile_ribbon()'s bands can overlap enough that the shaded fills merge into a single indistinguishable region, and its median lines – all styled identically – become the only way to tell the bands apart, which fails wherever two of them cross. ribbon_edges = TRUE mitigates this by drawing each band's own ci_lower/ci_upper bounds as a line (see edge_linetype/edge_linewidth/edge_colour), which stays legible even where the fills themselves are illegible.

See also

er_style_vpc(), er_style_vpc_observed()

Examples

if (requireNamespace("erglm", quietly = TRUE)) {
  library(erglm)
  mod <- erglm_model(ae2 ~ aucss + sex, erglm_data, family = binomial())

  # er_style_vpc_simulated_mean_errorbar(): the default, adaptive to
  # plot_by's type
  erglm_data |>
    er_vpc(aucss, ae2, plot_by = aucss) |>
    er_vpc_add_observed(style = er_style_vpc_observed_mean_errorbar) |>
    er_vpc_add_simulated(model = mod, seed = 6203, style = er_style_vpc_simulated_mean_errorbar) |>
    plot()

  # er_style_vpc_simulated_quantile_errorbar(): a point + interval per
  # requested percentile, paired with the matching observed builder
  mod2 <- erglm_model(biomarker_change ~ aucss, erglm_data, family = gaussian())
  erglm_data |>
    er_vpc(aucss, biomarker_change, plot_by = aucss) |>
    er_vpc_add_observed(style = er_style_vpc_observed_quantile_errorbar) |>
    er_vpc_add_simulated(
      model = mod2, seed = 8417, style = er_style_vpc_simulated_quantile_errorbar
    ) |>
    plot()
}