plot_ICATE: Plot Individual Conditional Average Treatment effects

In joemarlo/plotBart: Diagnostic and Plotting Functions to Supplement 'bartCause'

Plot Individual Conditional Average Treatment effects

Description

Plots a histogram of Individual Conditional Average Treatment effects (ICATE). ICATEs are the difference in each individual's predicted outcome under the treatment and predicted outcome under the control averaged over the individual. Plots of ICATEs are useful to identify potential heterogeneous treatment effects between different individuals. ICATE plots can be grouped by discrete variables.

Usage

plot_ICATE(.model, .group_by = NULL, n_bins = 30, .alpha = 0.7)

Arguments

.model	a model produced by 'bartCause::bartc()'
.group_by	a grouping variable as a vector
n_bins	number of bins
.alpha	transparency of histograms

Value

ggplot object

Author(s)

George Perrett

Examples

data(lalonde)
confounders <- c('age', 'educ', 'black', 'hisp', 'married', 'nodegr')
model_results <- bartCause::bartc(
 response = lalonde[['re78']],
 treatment = lalonde[['treat']],
 confounders = as.matrix(lalonde[, confounders]),
 estimand = 'ate',
 commonSup.rule = 'none'
)
plot_ICATE(model_results, lalonde$married)

joemarlo/plotBart documentation built on May 31, 2024, 12:22 p.m.