Diagnostic and Plotting Functions to Supplement 'bartCause'.

plotBart

plotBart is a diagnostic and plotting package for bartCause and thinkCausal.

library(plotBart)
data(lalonde)
confounders <- c('age', 'educ', 'black', 'hisp', 'married', 'nodegr')

# fit BART model
model_results <- bartCause::bartc(
  response = lalonde[['re78']],
  treatment = lalonde[['treat']],
  confounders = as.matrix(lalonde[, confounders]),
  estimand = 'ate',
  commonSup.rule = 'none',
  verbose = FALSE,
  keepTrees = TRUE
)

# plot common support
plot_common_support(.model = model_results)

# plot CATE and manipulate ggplot object
plot_CATE(
  .model = model_results, 
  type = 'density', 
  ci_80 = TRUE, 
  ci_95 = TRUE,
  .mean = TRUE
) + 
  labs(subtitle = 'My comments on the results') +
  theme_classic()

Installation

plotBart is currently in development and is available to test by installing via:

# install.packages("remotes")
remotes::install_github('priism-center/plotBart@*release')