Skip to contents

Auto-Bin a plot of a continuous moderating variable into a discrete moderating variable

Source: R/plot_moderators.R
plot_moderator_c_bin.Rd

Use a regression tree to optimally bin a continous variable

Usage

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

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

.name

sting representing the name of the moderating variable

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_c_bin(model_results, lalonde$age, .name = 'age')
#> Joining with `by = join_by(splits)`

# }