plot_var: Visualize Covariate Distribution Across TG, VCG, and POOL

In eVCGsampler: VCG Sampling using Energy-Based Covariate Balancing

Visualize Covariate Distribution Across TG, VCG, and POOL

Description

Creates a plot to compare the distribution of a selected variable across three groups: TG (treated groups), VCG (virtual control group), and POOL (data pool).

Usage

plot_var(data, what = NULL, stratum = "in_stratum", group = "VCG", title = "")

Arguments

data	A balanced data frame (output of the VCG_sampler function)
what	A string specifying the name of the variable to be visualized.
stratum	A string specifying the name of the stratum variable (default is '"in_stratum"')
group	A string specifying the column name used to define group membership (default is '"VCG"').
title	Optional title for the plot.

Details

The function uses energy distance to quantify distributional differences between groups. For continuous variables, it overlays dashed lines for TG group statistics (mean, min, max) and displays sample sizes. For categorical variables, it uses color-coded bars and cumulative proportion lines to highlight imbalance.

Value

A ggplot2 object showing either:

• A boxplot for continuous variables (more than 4 unique values).

• A proportional bar chart for categorical variables (2–4 unique values).

Examples

dat   <- data.frame(
  cov1  = rnorm(50, 10, 1),
  cov2  = rnorm(50, 7,  1),
  cov3  = rnorm(50, 5,  1),
  treated = rep(c(0, 1), c(35, 15))
)
  out <- VCG_sampler(treated ~ cov1 + cov2 + cov3, data=dat, n=5, plot=FALSE)
  plot_var(out, what='cov1', group='VCG')
  plot_var(out, what='cov2', group='VCG')

eVCGsampler documentation built on March 10, 2026, 5:07 p.m.