control_for: Adjust for variables and activate any biasing paths that...

In ggdag: Analyze and Create Elegant Directed Acyclic Graphs

Adjust for variables and activate any biasing paths that result

Description

Adjust for variables and activate any biasing paths that result

Usage

control_for(.tdy_dag, var, as_factor = TRUE, activate_colliders = TRUE, ...)

adjust_for(.tdy_dag, var, as_factor = TRUE, activate_colliders = TRUE, ...)

ggdag_adjust(
  .tdy_dag,
  var = NULL,
  ...,
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = text_col,
  node = TRUE,
  stylized = FALSE,
  text = TRUE,
  use_labels = NULL,
  collider_lines = TRUE
)

Arguments

.tdy_dag	input graph, an object of class tidy_dagitty or dagitty
var	a character vector, the variable(s) to adjust for.
as_factor	logical. Should the adjusted column be a factor?
activate_colliders	logical. Include colliders activated by adjustment?
...	additional arguments passed to tidy_dagitty()
node_size	size of DAG node
text_size	size of DAG text
label_size	size of label text
text_col	color of DAG text
label_col	color of label text
node	logical. Should nodes be included in the DAG?
stylized	logical. Should DAG nodes be stylized? If so, use geom_dag_nodes and if not use geom_dag_point
text	logical. Should text be included in the DAG?
use_labels	a string. Variable to use for geom_dag_repel_label(). Default is NULL.
collider_lines	logical. Should the plot show paths activated by adjusting for a collider?

Value

a tidy_dagitty with a adjusted column for adjusted variables, as well as any biasing paths that arise, or a ggplot

Examples

dag <- dagify(m ~ a + b, x ~ a, y ~ b)

control_for(dag, var = "m")
ggdag_adjust(dag, var = "m")

ggdag documentation built on May 31, 2023, 7:48 p.m.