hte_plot_line {htetree} | R Documentation |
Visualize the Estimated Results
Description
The function hte_plot_line
takes a model created by
causal tree, as well as the adjusted version, and plots the
different least squares models used to estimate heterogeneous
treatment effects(HTE) at each node. At each node, this
visualization aims to show how the estimated treatment effect
differs when using ordinary least squares and weighted least
squares methods. The weighted least squares method in this
package uses
inverse propensity scores as weights, in order to reduce
bias due to confounding variables.
Usage
hte_plot_line(
model,
data,
treatment_indicator = NULL,
outcomevariable,
propensity_score,
plot.title = "Visualization of the Tree",
gamma = 0,
lambda = 0,
...
)
Arguments
model |
a tree model constructed by |
data |
a data frame containing the variables in the model. |
treatment_indicator |
a character representing the column name for the treatment variable in the causal setup. |
outcomevariable |
a character representing the column name of the outcome variable. |
propensity_score |
a character representing the column name of the propensity score. |
plot.title |
character representing the main title of the plot. |
gamma , lambda |
numbers indicating the bias level used in sensitivity analysis |
... |
further arguments passed to or from other methods. |
Value
No return value, used for plotting the estimated results with lines.