plot_SATE: Plot histogram or density of Sample Average Treatment Effects

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

Plot histogram or density of Sample Average Treatment Effects

Description

Plot a histogram or density of the Sample Average Treatment Effect (SATE). The Sample Average Treatment Effect is derived from taking the difference of each individual's observed outcome and a predicted counterfactual outcome from a BART model averaged over the population. The mean of SATE will resemble means of CATE and PATE but will account for the least uncertainty.

Usage

plot_SATE(
  .model,
  type = c("histogram", "density"),
  ci_80 = FALSE,
  ci_95 = FALSE,
  reference = NULL,
  .mean = FALSE,
  .median = FALSE,
  check_overlap = FALSE,
  overlap_rule = c("none", "sd", "chisq")
)

Arguments

.model	a model produced by 'bartCause::bartc()'
type	histogram or density
ci_80	TRUE/FALSE. Show the 80% credible interval?
ci_95	TRUE/FALSE. Show the 95% credible interval?
reference	numeric. Show a vertical reference line at this x-axis value
.mean	TRUE/FALSE. Show the mean reference line
.median	TRUE/FALSE. Show the median reference line
check_overlap	TRUE/FALSE. Check if any overlap rules are applicable
overlap_rule	enter overlap rules to view how different bartCause removal rules would have influenced results. Only applicable if check_overlap is TRUE.

Value

ggplot object

Author(s)

George Perrett, Joseph Marlo

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_SATE(model_results)

joemarlo/plotBart documentation built on May 31, 2024, 12:22 p.m.