plot_ICATE {plotBart}

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)