View source: R/adjustment_sets.R
Adjust for variables | R Documentation |
Adjust for variables and activate any biasing paths that result
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,
...,
size = 1,
edge_type = c("link_arc", "link", "arc", "diagonal"),
node_size = 16,
text_size = 3.88,
label_size = text_size,
text_col = "white",
label_col = "black",
edge_width = 0.6,
edge_cap = 10,
arrow_length = 5,
use_edges = TRUE,
use_nodes = TRUE,
use_stylized = FALSE,
use_text = TRUE,
use_labels = FALSE,
text = NULL,
label = NULL,
node = deprecated(),
stylized = deprecated(),
collider_lines = TRUE
)
.tdy_dag |
input graph, an object of class |
var |
a character vector, the variable(s) to adjust for. |
as_factor |
logical. Should the |
activate_colliders |
logical. Include colliders activated by adjustment? |
... |
additional arguments passed to |
size |
A numeric value scaling the size of all elements in the DAG. This allows you to change the scale of the DAG without changing the proportions. |
edge_type |
The type of edge, one of "link_arc", "link", "arc", "diagonal". |
node_size |
The size of the nodes. |
text_size |
The size of the text. |
label_size |
The size of the labels. |
text_col |
The color of the text. |
label_col |
The color of the labels. |
edge_width |
The width of the edges. |
edge_cap |
The size of edge caps (the distance between the arrowheads and the node borders). |
arrow_length |
The length of arrows on edges. |
use_edges |
A logical value. Include a |
use_nodes |
A logical value. Include |
use_stylized |
A logical value. Include |
use_text |
A logical value. Include |
use_labels |
A logical value. Include |
text |
The bare name of a column to use for |
label |
The bare name of a column to use for |
node |
Deprecated. |
stylized |
Deprecated. |
collider_lines |
logical. Should the plot show paths activated by adjusting for a collider? |
a tidy_dagitty
with a adjusted
column for adjusted
variables, as well as any biasing paths that arise, or a ggplot
dag <- dagify(m ~ a + b, x ~ a, y ~ b)
control_for(dag, var = "m")
ggdag_adjust(dag, var = "m")
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