Batch Plot QINI Curves Across Treatment Costs for Multiple Models

Creates visualizations showing how QINI curves change with treatment cost for multiple models simultaneously. This function combines the functionality of margot_qini_cost_sensitivity() and margot_plot_qini_batch() to create comprehensive cost sensitivity visualizations.

Usage

margot_plot_qini_batch_cost_sensitivity(
  models,
  costs = c(0.2, 0.5, 1, 2, 5),
  model_names = NULL,
  plot_type = c("grid", "list", "combined"),
  spend_levels = 0.1,
  baseline_method = "maq_no_covariates",
  label_mapping = NULL,
  ncol = NULL,
  heights = NULL,
  widths = NULL,
  verbose = TRUE,
  x_axis = "budget",
  ...
)

Arguments

models

List returned by margot_causal_forest(), containing results and optionally full_models.

costs

Numeric vector of treatment costs to evaluate. Default is c(0.2, 0.5, 1, 2, 5) representing a range from cheap to expensive treatments.

model_names

Optional character vector specifying which models to process. Default NULL (all models).

plot_type

Character; how to arrange the plots: - "grid": Arrange in a grid with models as rows and costs as columns - "list": Return a nested list of individual plots - "combined": Create a single combined plot with facets Default is "grid".

spend_levels

Numeric vector of spend levels for annotations. Default is 0.1.

baseline_method

Method for generating baseline. See margot_qini() for details. Default is "maq_no_covariates".

label_mapping

Named character vector for converting variable names to readable labels.

ncol

For plot_type = "grid", number of columns in the grid. Default NULL uses the number of costs.

heights

For plot_type = "grid", relative heights of rows. Default NULL gives equal heights.

widths

For plot_type = "grid", relative widths of columns. Default NULL gives equal widths.

verbose

Logical; print progress messages (default TRUE).

x_axis

Type of x-axis for QINI curves: "proportion" or "budget" (default). "budget" shows budget per unit (matching maq visualization) which better illustrates the effect of different treatment costs.

...

Additional arguments passed to margot_plot_qini().

Value

Depending on plot_type: - "grid": A combined plot object (requires patchwork package) - "list": A nested list where first level is model names, second level is costs - "combined": A single ggplot object with facets

Details

This function efficiently generates QINI curves for multiple models at different treatment costs, enabling comprehensive cost sensitivity analysis. The plots help identify: - Which models are most sensitive to treatment cost - Cost thresholds where targeting becomes ineffective - Optimal cost-benefit trade-offs for different outcomes

Examples

if (FALSE) { # \dontrun{
# Create grid of plots for all models
grid_plots <- margot_plot_qini_batch_cost_sensitivity(
  cf_results,
  costs = c(0.5, 1, 2),
  plot_type = "grid"
)
print(grid_plots)

# Get individual plots as a list
plot_list <- margot_plot_qini_batch_cost_sensitivity(
  cf_results,
  costs = c(0.5, 1, 2),
  model_names = c("anxiety", "depression"),
  plot_type = "list"
)
# Access specific plot: plot_list$model_anxiety$cost_0.5

# Create combined faceted plot
combined_plot <- margot_plot_qini_batch_cost_sensitivity(
  cf_results,
  costs = c(0.5, 1, 2),
  model_names = c("anxiety", "depression"),
  plot_type = "combined"
)
} # }