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Plot the Conditional Average Treatment Effect conditional on a discrete moderator

Source: R/plot_moderators.R
plot_moderator_d.Rd

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(
  .model,
  moderator,
  type = c("density", "histogram", "errorbar"),
  .alpha = 0.7,
  facet = FALSE,
  .ncol = 1
)

Arguments

.model

a model produced by `bartCause::bartc()`

moderator

the moderator as a vector

type

string to specify if you would like to plot a histogram, density or error bar plot

.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

George Perrett

Examples

# \donttest{
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'
)
#> fitting treatment model via method 'bart'
#> fitting response model via method 'bart'
plot_moderator_d(model_results, lalonde$educ)

# }