Plot a waterfall of the ICATEs — plot

Plots the point and posterior intervals of each individual's ICATE ordered by the ICATE or a continuous variable. Points can be colored by a discrete variable. Waterfall plots are a useful visual diagnostic of possible treatment effect heterogeneity. A flat line implies little treatment effect heterogeneity while a steeper curve implies that the treatment effect varies across individuals in the sample. Ordering points by a continuous variable or coloring points by a discrete variable can be helpful to identify potential moderators of the treatment effect.

Usage

plot_waterfall(
  .model,
  descending = TRUE,
  .order = NULL,
  .color = NULL,
  .alpha = 0.5
)

Arguments

.model: a model produced by `bartCause::bartc()`
descending: order the ICATEs by value?
.order: a vector representing a custom order
.color: a vector representing colors
.alpha: transparency value [0, 1]

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_waterfall(model_results)

# }