Compute Difference in Gains and Integrated Difference Between Reference and Comparison Curves — margot_summary_cate_difference

This function computes the difference in average gains and the integrated difference between a reference curve (maq object) and a comparison curve at a specified spend level. It returns a list of formatted strings for easy use in Quarto markdown text.

Usage

margot_summary_cate_difference_gain(
  mc_result,
  outcome_var,
  reference_curve,
  comparison_curve,
  spend,
  digits = 3
)

Arguments

mc_result: A list containing the results from margot_multi_arm_causal_forest().
outcome_var: A character string specifying the name of the outcome variable.
reference_curve: A character string specifying the name of the reference Qini curve (e.g., "baseline").
comparison_curve: A character string specifying the name of the comparison Qini curve (e.g., "arm2").
spend: A numeric value specifying the spend level (between 0 and 1).
digits: An integer specifying the number of decimal places to round the output. Default is 3.

Value

A list containing formatted strings for use in Quarto markdown text:

diff_gain: Formatted string for difference in gains
int_diff: Formatted string for integrated difference
summary: A summary sentence of the comparison

Examples

if (FALSE) { # \dontrun{
# Assuming mc_result is the result of margot_multi_arm_causal_forest()
result <- margot_summary_cate_difference_gain(mc_result,
                                 outcome_var = "model_Y",
                                 reference_curve = "baseline",
                                 comparison_curve = "arm2",
                                 spend = 0.3)
# Use in text
glue::glue("The difference in gains is {result$diff_gain}. {result$summary}")
} # }