plot_moderator_d_density: Plot the Conditional Average Treatment Effect conditional on...

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

Plot the Conditional Average Treatment Effect conditional on a discrete moderator

Description

Plot the Conditional Average Treatment Effect split by a discrete moderating variable. This plot will provide a visual test of moderation by discrete variables.

Usage

plot_moderator_d_density(
  .model,
  moderator,
  .alpha = 0.7,
  facet = FALSE,
  .ncol = 1
)

Arguments

.model	a model produced by 'bartCause::bartc()'
moderator	the moderator as a vector
.alpha	transparency value [0, 1]
facet	TRUE/FALSE. Create panel plots of each moderator level?
.ncol	number of columns to use when faceting

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',
 commonSuprule = 'none'
)
plot_moderator_d_density(model_results, lalonde$educ)

plotBart documentation built on May 27, 2022, 9:12 a.m.