Covariate Adjustment Sets — Covariate Adjustment Sets • ggdag

See dagitty::adjustmentSets() for details.

Usage

dag_adjustment_sets(.tdy_dag, exposure = NULL, outcome = NULL, ...)

ggdag_adjustment_set(
  .tdy_dag,
  exposure = NULL,
  outcome = NULL,
  ...,
  shadow = TRUE,
  size = 1,
  node_size = ggdag_option("node_size", 16),
  text_size = ggdag_option("text_size", 3.88),
  label_size = ggdag_option("label_size", text_size),
  text_col = ggdag_option("text_col", "white"),
  label_col = ggdag_option("label_col", "black"),
  edge_width = ggdag_option("edge_width", 0.6),
  edge_cap = ggdag_option_proportional("edge_cap", 8, 10),
  arrow_length = ggdag_option("arrow_length", 5),
  use_edges = ggdag_option("use_edges", TRUE),
  use_nodes = ggdag_option("use_nodes", TRUE),
  use_stylized = ggdag_option("use_stylized", FALSE),
  use_text = ggdag_option("use_text", TRUE),
  use_labels = ggdag_option("use_labels", FALSE),
  label_geom = ggdag_option("label_geom", geom_dag_label_repel),
  unified_legend = TRUE,
  key_glyph = draw_key_dag_point,
  label = NULL,
  text = NULL,
  edge_engine = ggdag_option("edge_engine", "ggraph"),
  node = deprecated(),
  stylized = deprecated(),
  expand_x = expansion(c(0.25, 0.25)),
  expand_y = expansion(c(0.2, 0.2))
)

Arguments

.tdy_dag: A tidy_dagitty or dagitty object
exposure: A character vector, the exposure variable. Default is NULL, in which case it will be determined from the DAG.
outcome: A character vector, the outcome variable. Default is NULL, in which case it will be determined from the DAG.
...: additional arguments to adjustmentSets
shadow: logical. Show paths blocked by adjustment?
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.
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 geom_dag_edges*() function? If TRUE, which is determined by edge_type.
use_nodes: A logical value. Include geom_dag_point()?
use_stylized: A logical value. Include geom_dag_node()?
use_text: A logical value. Include geom_dag_text()?
use_labels: A logical value. Include a label geom? The specific geom used is controlled by label_geom.
label_geom: A geom function to use for drawing labels when use_labels = TRUE. Default is geom_dag_label_repel. Other options include geom_dag_label, geom_dag_text_repel, geom_dag_label_repel2, and geom_dag_text_repel2.
unified_legend: A logical value. When TRUE and both use_edges and use_nodes are TRUE, creates a unified legend entry showing both nodes and edges in a single key, and hides the separate edge legend. This creates a single, more compact legend. Default is TRUE.
key_glyph: A function to use for drawing the legend key glyph for nodes. If NULL (the default), the glyph is chosen automatically based on the unified_legend setting. When provided, this overrides the automatic selection. Common options include draw_key_dag_point, draw_key_dag_combined, and draw_key_dag_collider.
label: The bare name of a column to use for labels. If use_labels = TRUE, the default is to use label.
text: The bare name of a column to use for geom_dag_text(). If use_text = TRUE, the default is to use name.
edge_engine: The engine used to draw edges. Either "ggraph" (default) or "ggarrow". When "ggarrow", edges are drawn using ggarrow geoms, which support additional customization via the arrow_head, arrow_fins, arrow_mid, and curvature global options (see ggdag_options_set()).
node: Deprecated.
stylized: Deprecated.
expand_x, expand_y: Vector of range expansion constants used to add some padding around the data, to ensure that they are placed some distance away from the axes. Use the convenience function ggplot2::expansion() to generate the values for the expand argument.

Value

a tidy_dagitty with an adjusted column and set column, indicating adjustment status and DAG ID, respectively, for the adjustment sets or a ggplot

Edge layers of the composite plotters

The plotters that color or fade edges by an analysis column build their edge layers themselves, and which layers they build is settled from the DAG they are called with: a DAG with no bidirected edge is given no bidirected edge layer. Replacing the data of the returned plot afterwards, with ggplot2's %+%, does not bring a layer back, so a plot built for one DAG is not a template for another.

Examples

dag <- dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  w1 ~ ~w2,
  exposure = "x",
  outcome = "y"
)

tidy_dagitty(dag) |> dag_adjustment_sets()
#> # DAG:
#> # A `dagitty` DAG with: 7 nodes and 11 edges
#> # Exposure: x
#> # Outcome: y
#> # Adjustment sets: 3 sets: {w1, w2, z2}, {v, w1}, {w1, z1}
#> #
#> # Data:
#> # A tibble: 36 × 9
#>    name        x       y direction to       xend    yend adjusted   set         
#>    <chr>   <dbl>   <dbl> <fct>     <chr>   <dbl>   <dbl> <chr>      <chr>       
#>  1 v     -0.631   1.36   ->        z1     0.659   0.796  unadjusted {w1, w2, z2}
#>  2 v     -0.631   1.36   ->        z2    -1.17    0.104  unadjusted {w1, w2, z2}
#>  3 w1     0.633  -0.658  ->        x      1.29   -0.0707 adjusted   {w1, w2, z2}
#>  4 w1     0.633  -0.658  ->        y     -0.0837 -0.441  adjusted   {w1, w2, z2}
#>  5 w1     0.633  -0.658  ->        z1     0.659   0.796  adjusted   {w1, w2, z2}
#>  6 w1     0.633  -0.658  <->       w2    -0.700  -1.09   adjusted   {w1, w2, z2}
#>  7 w2    -0.700  -1.09   ->        y     -0.0837 -0.441  adjusted   {w1, w2, z2}
#>  8 w2    -0.700  -1.09   ->        z2    -1.17    0.104  adjusted   {w1, w2, z2}
#>  9 x      1.29   -0.0707 ->        y     -0.0837 -0.441  unadjusted {w1, w2, z2}
#> 10 y     -0.0837 -0.441  NA        NA    NA      NA      unadjusted {w1, w2, z2}
#> # ℹ 26 more rows
#> #
#> # ℹ Use `pull_dag() (`?pull_dag`)` to retrieve the DAG object and `pull_dag_data() (`?pull_dag_data`)` for the data frame

ggdag_adjustment_set(dag)


ggdag_adjustment_set(
  dagitty::randomDAG(10, 0.5),
  exposure = "x3",
  outcome = "x5"
)