Plot an effective-data-points diagnostic

Draws one view of a check_edp() result. type = "boxplot", the default, boxes EDP by intervention. Its whiskers reach the fifth and the ninety-fifth percentile, following Ring and Schomaker (2026) rather than Tukey's fences, and the values outside them are drawn as points. For the estimator variant it draws the outcome-model and the treatment-model measure side by side in a facet per intervention. type = "histogram" shows the distribution of EDP faceted by intervention, type = "ecdf" shows its empirical cumulative distribution colored by intervention, and type = "density" draws one density ridgeline per intervention, which needs the ggridges package. Each of those three draws one measure: edp for the data variant and edp_outcome for the estimator variant, the measure carrying the exposure dimension and so the one an intervention moves. type = "scatter" plots edp_outcome against edp_treatment colored by ideal_weight; it needs the estimator variant and aborts for the data variant. pull_plot_data() returns the tibble any of these views draws.

Arguments

object

An edp_result from check_edp().

type

One of "boxplot", "histogram", "ecdf", "density", or "scatter".

...

Not used.

Value

A ggplot2::ggplot object.

Examples

set.seed(1)
n <- 100
x1 <- rnorm(n)
dose <- rnorm(n, mean = x1)
df <- data.frame(dose = dose, x1 = x1)
result <- check_edp(df, dose, x1, values = c(0, 1), exposure_type = "continuous")

autoplot(result)

autoplot(result, type = "histogram")

autoplot(result, type = "ecdf")