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 = FALSE,
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,
expand_x = expansion(c(0.25, 0.25)),
expand_y = expansion(c(0.2, 0.2))
)
Arguments
- .tdy_dag
input graph, an object of class
tidy_dagitty
ordagitty
- 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?
- 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 usegeom_dag_point
- text
logical. Should text be included in the DAG?
- use_labels
a string. Variable to use for
geom_dag_label_repel()
. Default isNULL
.- 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
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()
#> # A DAG with 7 nodes and 33 edges
#> #
#> # Exposure: x
#> # Outcome: y
#> #
#> # A tibble: 36 × 10
#> name x y direction to xend yend circular adjusted set
#> <chr> <dbl> <dbl> <fct> <chr> <dbl> <dbl> <lgl> <chr> <chr>
#> 1 v 2.18 0.0732 -> z1 0.946 -0.595 FALSE unadjusted {w1, w…
#> 2 v 2.18 0.0732 -> z2 2.83 -1.13 FALSE unadjusted {w1, w…
#> 3 w1 1.10 -2.04 -> x 0.387 -1.51 FALSE adjusted {w1, w…
#> 4 w1 1.10 -2.04 -> y 1.79 -1.76 FALSE adjusted {w1, w…
#> 5 w1 1.10 -2.04 -> z1 0.946 -0.595 FALSE adjusted {w1, w…
#> 6 w1 1.10 -2.04 <-> w2 2.46 -2.36 FALSE adjusted {w1, w…
#> 7 w2 2.46 -2.36 -> y 1.79 -1.76 FALSE adjusted {w1, w…
#> 8 w2 2.46 -2.36 -> z2 2.83 -1.13 FALSE adjusted {w1, w…
#> 9 x 0.387 -1.51 -> y 1.79 -1.76 FALSE unadjusted {w1, w…
#> 10 y 1.79 -1.76 NA NA NA NA FALSE unadjusted {w1, w…
#> # ℹ 26 more rows
ggdag_adjustment_set(dag)
ggdag_adjustment_set(dagitty::randomDAG(10, .5),
exposure = "x3",
outcome = "x5"
)