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Classify DAG edges as backdoor or direct

Source: R/paths.R
edge_backdoor.Rd

edge_backdoor() identifies edges as being on backdoor paths or direct causal paths between an exposure and outcome. This function adds edge-level information to the tidy DAG object, classifying each edge based on the types of paths it appears on.

Usage

edge_backdoor(
  .dag,
  from = NULL,
  to = NULL,
  adjust_for = NULL,
  open_only = TRUE,
  ...
)

Arguments

.dag

A tidy_dagitty or dagitty object

from

A character vector with starting node name(s), or NULL. If NULL, checks DAG for exposure variable.

to

A character vector with ending node name(s), or NULL. If NULL, checks DAG for outcome variable.

adjust_for

character vector, a set of variables to control for. Default is NULL.

open_only

logical. If TRUE (default), only considers open paths. If FALSE, includes information about closed paths as well.

...

additional arguments passed to tidy_dagitty()

Value

A tidy_dagitty object with additional columns:

  • path_type: "direct", "backdoor", "other", or "both" classification for each edge

  • open: logical indicating if the edge is part of an open path

Details

Edges are classified by examining the paths between exposure and outcome:

  • Direct edges appear only on directed causal paths

  • Backdoor edges appear only on backdoor paths, whose first edge points into the exposure

  • Other edges appear only on paths that are neither causal nor backdoor, such as a path through a collider

  • Both edges appear on more than one of those kinds of path

When open_only = TRUE (default), path_type will be NA for edges that are only part of closed paths.

Examples

# Create a DAG with both direct and backdoor paths
dag <- dagify(
  y ~ x + z,
  x ~ z,
  exposure = "x",
  outcome = "y"
)

# Classify edges
edge_backdoor(dag)
#> # DAG:
#> # A `dagitty` DAG with: 3 nodes and 3 edges
#> # Exposure: x
#> # Outcome: y
#> #
#> # Data:
#> # A tibble: 4 × 9
#>   name          x      y direction to      xend   yend path_type open 
#>   <chr>     <dbl>  <dbl> <fct>     <chr>  <dbl>  <dbl> <chr>     <lgl>
#> 1 x      5.01e- 1  0.289 ->        y     -0.501  0.289 direct    TRUE 
#> 2 y     -5.01e- 1  0.289 NA        NA    NA     NA     NA        NA   
#> 3 z     -9.60e-11 -0.579 ->        x      0.501  0.289 backdoor  TRUE 
#> 4 z     -9.60e-11 -0.579 ->        y     -0.501  0.289 backdoor  TRUE 
#> #
#> # ℹ Use `pull_dag() (`?pull_dag`)` to retrieve the DAG object and `pull_dag_data() (`?pull_dag_data`)` for the data frame

# Include closed paths
edge_backdoor(dag, open_only = FALSE)
#> # DAG:
#> # A `dagitty` DAG with: 3 nodes and 3 edges
#> # Exposure: x
#> # Outcome: y
#> #
#> # Data:
#> # A tibble: 4 × 9
#>   name          x      y direction to      xend   yend path_type open 
#>   <chr>     <dbl>  <dbl> <fct>     <chr>  <dbl>  <dbl> <chr>     <lgl>
#> 1 x      5.02e- 1  0.290 ->        y     -0.502  0.290 direct    TRUE 
#> 2 y     -5.02e- 1  0.290 NA        NA    NA     NA     NA        NA   
#> 3 z      1.13e-10 -0.580 ->        x      0.502  0.290 backdoor  TRUE 
#> 4 z      1.13e-10 -0.580 ->        y     -0.502  0.290 backdoor  TRUE 
#> #
#> # ℹ Use `pull_dag() (`?pull_dag`)` to retrieve the DAG object and `pull_dag_data() (`?pull_dag_data`)` for the data frame