Package 'ggdag' reference manual

Title:	Analyze and Create Elegant Directed Acyclic Graphs
Description:	Tidy, analyze, and plot directed acyclic graphs (DAGs). 'ggdag' is built on top of 'dagitty', an R package that uses the 'DAGitty' web tool (<https://dagitty.net/>) for creating and analyzing DAGs. 'ggdag' makes it easy to tidy and plot 'dagitty' objects using 'ggplot2' and 'ggraph', as well as common analytic and graphical functions, such as determining adjustment sets and node relationships.
Authors:	Malcolm Barrett [aut, cre]
Maintainer:	Malcolm Barrett <[email protected]>
License:	MIT + file LICENSE
Version:	0.2.13.9000
Built:	2024-11-05 05:29:48 UTC
Source:	https://github.com/r-causal/ggdag

Activate paths opened by stratifying on a collider

Description

Stratifying on colliders can open biasing pathways between variables. activate_collider_paths activates any such pathways given a variable or set of variables to adjust for and adds them to the tidy_dagitty.

Usage

activate_collider_paths(.tdy_dag, adjust_for, ...)
activate_collider_paths(.tdy_dag, adjust_for, ...)

Arguments

`.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`adjust_for`	a character vector, the variable(s) to adjust for.
`...`	additional arguments passed to `tidy_dagitty()`

Value

a tidy_dagitty with additional rows for collider-activated pathways

Examples

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

collided_dag <- activate_collider_paths(dag, adjust_for = "m")
collided_dag

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

collided_dag <- activate_collider_paths(dag, adjust_for = "m")
collided_dag

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,
  ...,
  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
)
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
)

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()`
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.
`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")

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

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

Define Aesthetics for Directed Acyclic Graphs (DAGs)

Description

aes_dag() is a wrapper around aes() that specifies x, y, xend, and yend, which are required for most DAG visualizations. It merges any additional aesthetics, e.g. color or shape, with the default aesthetic mappings.

Usage

aes_dag(...)
aes_dag(...)

Arguments

...

Additional aesthetic mappings passed as arguments. These can include any aesthetic supported by ggplot2 (e.g., color, size, shape).

Value

A ggplot2 aesthetic mapping object that includes both the default DAG aesthetics and any user-specified aesthetics.

Examples

library(ggplot2)
confounder_triangle() %>%
  dag_adjustment_sets() %>%
  ggplot(aes_dag(color = adjusted)) +
  geom_dag() +
  facet_wrap(~set)

library(ggplot2)
confounder_triangle() %>%
  dag_adjustment_sets() %>%
  ggplot(aes_dag(color = adjusted)) +
  geom_dag() +
  facet_wrap(~set)

Convert DAGS to tidygraph

Description

A thin wrapper to convert tidy_dagitty and dagitty objects to tbl_graph, which can then be used to work in tidygraph and ggraph directly. See tidygraph::as_tbl_graph().

Usage

## S3 method for class 'tidy_dagitty'
as_tbl_graph(x, directed = TRUE, ...)

## S3 method for class 'dagitty'
as_tbl_graph(x, directed = TRUE, ...)
## S3 method for class 'tidy_dagitty'
as_tbl_graph(x, directed = TRUE, ...)

## S3 method for class 'dagitty'
as_tbl_graph(x, directed = TRUE, ...)

Arguments

`x`	an object of class `tidy_dagitty` or `dagitty`
`directed`	logical. Should the constructed graph be directed? Default is `TRUE`
`...`	other arguments passed to `as_tbl_graph`

Value

a tbl_graph

Examples


library(ggraph)
library(tidygraph)
butterfly_bias() %>%
  as_tbl_graph() %>%
  ggraph() +
  geom_edge_diagonal() +
  geom_node_point()

library(ggraph)
library(tidygraph)
butterfly_bias() %>%
  as_tbl_graph() %>%
  ggraph() +
  geom_edge_diagonal() +
  geom_node_point()

Convert objects into `tidy_dagitty` objects

Description

An alternative API and specification to tidy_dagitty(), as_tidy_dagitty() allows you to create tidy_dagitty objects from data frames and lists. There is also a method for dagitty objects, which is a thin wrapper for tidy_dagitty(). To create a DAG from a list, each element of the list should be a character vector, and the order of the elements should be the time order in which they appear in the DAG, e.g. element 1 occurs at time point 1. To create a DAG from a data frame, it must contain name and to columns, representing the nodes and any edges leading from the nodes. If there are x, y, xend, and yend columns, they will be used as coordinates. Otherwise, layout will be used. See tidy_dagitty for more information about layouts. Additionally, you can specify status (one of exposure, outcome, or latent) by including a status column. Any other columns in the data set will also be joined to the tidy_dagitty data.

Usage

as_tidy_dagitty(x, ...)

## S3 method for class 'dagitty'
as_tidy_dagitty(x, seed = NULL, layout = "nicely", ...)

## S3 method for class 'data.frame'
as_tidy_dagitty(
  x,
  exposure = NULL,
  outcome = NULL,
  latent = NULL,
  labels = NULL,
  coords = NULL,
  seed = NULL,
  layout = "nicely",
  saturate = FALSE,
  ...
)

## S3 method for class 'list'
as_tidy_dagitty(
  x,
  exposure = NULL,
  outcome = NULL,
  latent = NULL,
  labels = NULL,
  coords = NULL,
  seed = NULL,
  layout = "time_ordered",
  ...
)
as_tidy_dagitty(x, ...)

## S3 method for class 'dagitty'
as_tidy_dagitty(x, seed = NULL, layout = "nicely", ...)

## S3 method for class 'data.frame'
as_tidy_dagitty(
  x,
  exposure = NULL,
  outcome = NULL,
  latent = NULL,
  labels = NULL,
  coords = NULL,
  seed = NULL,
  layout = "nicely",
  saturate = FALSE,
  ...
)

## S3 method for class 'list'
as_tidy_dagitty(
  x,
  exposure = NULL,
  outcome = NULL,
  latent = NULL,
  labels = NULL,
  coords = NULL,
  seed = NULL,
  layout = "time_ordered",
  ...
)

Arguments

`x`	An object to convert into a `tidy_dagitty`. Currently supports `dagitty` and `data.frame` objects.
`...`	optional arguments passed to `ggraph::create_layout()`
`seed`	a numeric seed for reproducible layout generation
`layout`	a layout available in `ggraph`. See `ggraph::create_layout()` for details. Alternatively, `"time_ordered"` will use `time_ordered_coords()` to algorithmically sort the graph by time.
`exposure`	a character vector for the exposure (must be a variable name in the DAG)
`outcome`	a character vector for the outcome (must be a variable name in the DAG)
`latent`	a character vector for any latent variables (must be a variable name in the DAG)
`labels`	a named character vector, labels for variables in the DAG
`coords`	coordinates for the DAG nodes. Can be a named list or a `data.frame` with columns x, y, and name
`saturate`	Logical. Saturate the DAG such that there is an edge going from every point in the future from a given node? Setting this to `TRUE` will potentially lead to more edges than present in `x`.

Value

a tidy_dagitty object

Examples


data.frame(name = c("c", "c", "x"), to = c("x", "y", "y")) %>%
  as_tidy_dagitty()

time_points <- list(c("a", "b", "c"), "d", c("e", "f", "g"), "z")

time_points %>%
  # create a saturated, time-ordered DAG
  as_tidy_dagitty() %>%
  # remove the edge from `c` to `f`
  dag_prune(c("c" = "f"))

data.frame(name = c("c", "c", "x"), to = c("x", "y", "y")) %>%
  as_tidy_dagitty()

time_points <- list(c("a", "b", "c"), "d", c("e", "f", "g"), "z")

time_points %>%
  # create a saturated, time-ordered DAG
  as_tidy_dagitty() %>%
  # remove the edge from `c` to `f`
  dag_prune(c("c" = "f"))

Convert a `tidy_dagitty` object to data.frame

Description

Convert a tidy_dagitty object to data.frame

Usage

## S3 method for class 'tidy_dagitty'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)
## S3 method for class 'tidy_dagitty'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

Arguments

`x`	an object of class `tidy_dagitty`
`row.names`	NULL or a character vector giving the row names for the data frame. Missing values are not allowed.
`optional`	logical. If TRUE, setting row names and converting column names (to syntactic names: see make.names) is optional. Note that all of R's base package `as.data.frame()` methods use optional only for column names treatment, basically with the meaning of `⁠data.frame(*, check.names = !optional)⁠`
`...`	optional arguments passed to `as.data.frame()`

Convert a `tidy_dagitty` object to tbl

Description

Convert a tidy_dagitty object to tbl

Usage

## S3 method for class 'tidy_daggity'
as.tbl(x, row.names = NULL, optional = FALSE, ...)

## S3 method for class 'tidy_daggity'
as_tibble(x, row.names = NULL, optional = FALSE, ...)
## S3 method for class 'tidy_daggity'
as.tbl(x, row.names = NULL, optional = FALSE, ...)

## S3 method for class 'tidy_daggity'
as_tibble(x, row.names = NULL, optional = FALSE, ...)

Arguments

`x`	an object of class `tidy_dagitty`
`row.names`	NULL or a character vector giving the row names for the data frame. Missing values are not allowed.
`optional`	logical. If TRUE, setting row names and converting column names (to syntactic names: see make.names) is optional. Note that all of R's base package `as.data.frame()` methods use optional only for column names treatment, basically with the meaning of `⁠data.frame(*, check.names = !optional)⁠`
`...`	optional arguments passed to `dplyr::as_tibble()`

D-relationship between variables

Description

D-separation is a key concept in causal structural models. Variables are d-separated if there are no open paths between them. The ⁠node_d*()⁠ functions label variables as d-connected or d-separated. The ⁠ggdag_d*()⁠ functions plot the results. The ⁠*_dconnected()⁠, ⁠*_dseparated()⁠, and ⁠*_drelationship()⁠ functions essentially produce the same output and are just different ways of thinking about the relationship. See dagitty::dseparated() for details.

Usage

node_dconnected(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  as_factor = TRUE,
  ...
)

node_dseparated(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  as_factor = TRUE
)

node_drelationship(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  as_factor = TRUE
)

ggdag_drelationship(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  ...,
  edge_type = "link_arc",
  size = 1,
  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,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  collider_lines = TRUE
)

ggdag_dseparated(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  ...,
  edge_type = "link_arc",
  size = 1,
  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_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = FALSE,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  collider_lines = TRUE
)

ggdag_dconnected(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  ...,
  edge_type = "link_arc",
  size = 1,
  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_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = FALSE,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  collider_lines = TRUE
)
node_dconnected(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  as_factor = TRUE,
  ...
)

node_dseparated(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  as_factor = TRUE
)

node_drelationship(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  as_factor = TRUE
)

ggdag_drelationship(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  ...,
  edge_type = "link_arc",
  size = 1,
  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,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  collider_lines = TRUE
)

ggdag_dseparated(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  ...,
  edge_type = "link_arc",
  size = 1,
  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_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = FALSE,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  collider_lines = TRUE
)

ggdag_dconnected(
  .tdy_dag,
  from = NULL,
  to = NULL,
  controlling_for = NULL,
  ...,
  edge_type = "link_arc",
  size = 1,
  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_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = FALSE,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  collider_lines = TRUE
)

Arguments

`.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`from`	a character vector, the starting variable (must by in DAG). If `NULL`, checks DAG for exposure variable.
`to`	a character vector, the ending variable (must by in DAG). If `NULL`, checks DAG for outcome variable.
`controlling_for`	a character vector, variables in the DAG to control for.
`as_factor`	logical. Should the `d_relationship` variable be a factor?
`...`	additional arguments passed to `tidy_dagitty()`
`edge_type`	The type of edge, one of "link_arc", "link", "arc", "diagonal".
`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 `geom_dag_label_repel()`?
`label`	The bare name of a column to use for `geom_dag_label_repel()`. 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`.
`node`	Deprecated.
`stylized`	Deprecated.
`collider_lines`	logical. Should the plot show paths activated by adjusting for a collider?

Value

a tidy_dagitty with a d_relationship column for variable D relationship or a ggplot

Examples

library(ggplot2)
dag <- dagify(m ~ x + y)
dag %>% ggdag_drelationship("x", "y")
dag %>% ggdag_drelationship("x", "y", controlling_for = "m")

dag %>%
  node_dseparated("x", "y") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted, col = d_relationship)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  theme_dag() +
  scale_adjusted()

dag %>%
  node_dconnected("x", "y", controlling_for = "m") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted, col = d_relationship)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  theme_dag() +
  scale_adjusted()

dagify(m ~ x + y, m_jr ~ m) %>%
  tidy_dagitty(layout = "nicely") %>%
  node_dconnected("x", "y", controlling_for = "m_jr") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted, col = d_relationship)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  theme_dag() +
  scale_adjusted()
library(ggplot2)
dag <- dagify(m ~ x + y)
dag %>% ggdag_drelationship("x", "y")
dag %>% ggdag_drelationship("x", "y", controlling_for = "m")

dag %>%
  node_dseparated("x", "y") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted, col = d_relationship)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  theme_dag() +
  scale_adjusted()

dag %>%
  node_dconnected("x", "y", controlling_for = "m") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted, col = d_relationship)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  theme_dag() +
  scale_adjusted()

dagify(m ~ x + y, m_jr ~ m) %>%
  tidy_dagitty(layout = "nicely") %>%
  node_dconnected("x", "y", controlling_for = "m_jr") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted, col = d_relationship)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  theme_dag() +
  scale_adjusted()

Familial relationships between variables

Description

Parents and children are those nodes that either directly cause or are caused by the variable, respectively. Ancestors and descendants are those nodes that are on the path to or descend from the variable. The ⁠node_*()⁠ functions label variables depending on their relationship. The ⁠ggdag_*()⁠ functions plot the results. See dagitty::children for details.

Usage

node_children(.tdy_dag, .var, as_factor = TRUE)

node_parents(.tdy_dag, .var, as_factor = TRUE)

node_ancestors(.tdy_dag, .var, as_factor = TRUE)

node_descendants(.tdy_dag, .var, as_factor = TRUE)

node_markov_blanket(.tdy_dag, .var, as_factor = TRUE)

node_adjacent(.tdy_dag, .var, as_factor = TRUE)

ggdag_children(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_parents(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_ancestors(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_descendants(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_markov_blanket(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_adjacent(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)
node_children(.tdy_dag, .var, as_factor = TRUE)

node_parents(.tdy_dag, .var, as_factor = TRUE)

node_ancestors(.tdy_dag, .var, as_factor = TRUE)

node_descendants(.tdy_dag, .var, as_factor = TRUE)

node_markov_blanket(.tdy_dag, .var, as_factor = TRUE)

node_adjacent(.tdy_dag, .var, as_factor = TRUE)

ggdag_children(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_parents(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_ancestors(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_descendants(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_markov_blanket(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

ggdag_adjacent(
  .tdy_dag,
  .var,
  ...,
  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 = 8,
  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()
)

Arguments

`.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`.var`	a character vector, the variable to be assessed (must by in DAG)
`as_factor`	logical. Should the relationship variable be a factor?
`...`	additional arguments passed to `tidy_dagitty()`
`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`	a character vector, the edge geom to use. One of: "link_arc", which accounts for directed and bidirected edges, "link", "arc", or "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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a tidy_dagitty with an column related to the given relationship for variable D relationship or a ggplot

Examples

library(ggplot2)
dag <- dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  w1 ~ ~w2
)

ggdag_children(dag, "w1")

dag %>%
  node_children("w1") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, color = children)) +
  geom_dag_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  geom_dag_label_repel(aes(label = children, fill = children), col = "white", show.legend = FALSE) +
  theme_dag() +
  scale_adjusted() +
  scale_color_hue(breaks = c("parent", "child"))

ggdag_parents(dag, "y")

ggdag_ancestors(dag, "x")

ggdag_descendants(dag, "w1")

dag %>%
  node_parents("y") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, color = parent)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text(col = "white") +
  geom_dag_label_repel(aes(label = parent, fill = parent), col = "white", show.legend = FALSE) +
  theme_dag() +
  scale_adjusted() +
  scale_color_hue(breaks = c("parent", "child"))

library(ggplot2)
dag <- dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  w1 ~ ~w2
)

ggdag_children(dag, "w1")

dag %>%
  node_children("w1") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, color = children)) +
  geom_dag_edges() +
  geom_dag_node() +
  geom_dag_text(col = "white") +
  geom_dag_label_repel(aes(label = children, fill = children), col = "white", show.legend = FALSE) +
  theme_dag() +
  scale_adjusted() +
  scale_color_hue(breaks = c("parent", "child"))

ggdag_parents(dag, "y")

ggdag_ancestors(dag, "x")

ggdag_descendants(dag, "w1")

dag %>%
  node_parents("y") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, color = parent)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text(col = "white") +
  geom_dag_label_repel(aes(label = parent, fill = parent), col = "white", show.legend = FALSE) +
  theme_dag() +
  scale_adjusted() +
  scale_color_hue(breaks = c("parent", "child"))

Canonicalize a DAG

Description

Takes an input graph with bidirected edges and replaces every bidirected edge x <-> y with a substructure x <- L -> y, where L is a latent variable. See dagitty::canonicalize() for details. Undirected edges are not currently supported in ggdag.

Usage

node_canonical(.dag, ...)

ggdag_canonical(
  .tdy_dag,
  ...,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = text_col,
  use_edges = TRUE,
  use_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = NULL,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated()
)
node_canonical(.dag, ...)

ggdag_canonical(
  .tdy_dag,
  ...,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = text_col,
  use_edges = TRUE,
  use_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = NULL,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated()
)

Arguments

`.dag`, `.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`...`	additional arguments passed to `tidy_dagitty()`
`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.
`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 `geom_dag_label_repel()`?
`label`	The bare name of a column to use for `geom_dag_label_repel()`. 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`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a tidy_dagitty that includes L or a ggplot

Examples

dag <- dagify(y ~ x + z, x ~ ~z)

ggdag(dag)

node_canonical(dag)
ggdag_canonical(dag)

dag <- dagify(y ~ x + z, x ~ ~z)

ggdag(dag)

node_canonical(dag)
ggdag_canonical(dag)

Find colliders

Description

Detects any colliders given a DAG. node_collider tags colliders and ggdag_collider plots all exogenous variables.

Usage

node_collider(.dag, as_factor = TRUE, ...)

ggdag_collider(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)
node_collider(.dag, as_factor = TRUE, ...)

ggdag_collider(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)

Arguments

`.dag`, `.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`as_factor`	treat `collider` variable as factor
`...`	additional arguments passed to `tidy_dagitty()`
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a tidy_dagitty with a collider column for colliders or a ggplot

Examples

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

node_collider(dag)
ggdag_collider(dag)

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

node_collider(dag)
ggdag_collider(dag)

Manipulate DAG coordinates

Description

Manipulate DAG coordinates

Usage

coords2df(coord_list)

coords2list(coord_df)
coords2df(coord_list)

coords2list(coord_df)

Arguments

`coord_list`	a named list of coordinates
`coord_df`	a data.frame with columns x, y, and name

Value

either a list or a data.frame with DAG node coordinates

Examples

library(dagitty)
coords <- list(
  x = c(A = 1, B = 2, D = 3, C = 3, F = 3, E = 4, G = 5, H = 5, I = 5),
  y = c(A = 0, B = 0, D = 1, C = 0, F = -1, E = 0, G = 1, H = 0, I = -1)
)
coord_df <- coords2df(coords)
coords2list(coord_df)

x <- dagitty("dag{
             G <-> H <-> I <-> G
             D <- B -> C -> I <- F <- B <- A
             H <- E <- C -> G <- D
             }")
coordinates(x) <- coords2list(coord_df)

library(dagitty)
coords <- list(
  x = c(A = 1, B = 2, D = 3, C = 3, F = 3, E = 4, G = 5, H = 5, I = 5),
  y = c(A = 0, B = 0, D = 1, C = 0, F = -1, E = 0, G = 1, H = 0, I = -1)
)
coord_df <- coords2df(coords)
coords2list(coord_df)

x <- dagitty("dag{
             G <-> H <-> I <-> G
             D <- B -> C -> I <- F <- B <- A
             H <- E <- C -> G <- D
             }")
coordinates(x) <- coords2list(coord_df)

Covariate Adjustment Sets

Description

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 = 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,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  expand_x = expansion(c(0.25, 0.25)),
  expand_y = expansion(c(0.2, 0.2))
)
dag_adjustment_sets(.tdy_dag, exposure = NULL, outcome = NULL, ...)

ggdag_adjustment_set(
  .tdy_dag,
  exposure = NULL,
  outcome = NULL,
  ...,
  shadow = TRUE,
  size = 1,
  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,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated(),
  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` or `dagitty`
`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 `geom_dag_label_repel()`?
`label`	The bare name of a column to use for `geom_dag_label_repel()`. 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`.
`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

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()

ggdag_adjustment_set(dag)

ggdag_adjustment_set(
  dagitty::randomDAG(10, .5),
  exposure = "x3",
  outcome = "x5"
)

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()

ggdag_adjustment_set(dag)

ggdag_adjustment_set(
  dagitty::randomDAG(10, .5),
  exposure = "x3",
  outcome = "x5"
)

Create a dagitty DAG

Description

A convenience wrapper for dagitty::dagitty().

Usage

dag(...)
dag(...)

Arguments

...

a character vector in the style of dagitty. See dagitty::dagitty for details.

Value

a dagitty

Examples

dag("{x m} -> y")

dag("{x m} -> y")

Directed DAG edges

Description

Directed DAG edges

Usage

geom_dag_edges_link(
  mapping = NULL,
  data = NULL,
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

geom_dag_edges_arc(
  mapping = NULL,
  data = NULL,
  curvature = 0.5,
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  fold = FALSE,
  n = 100,
  lineend = "butt",
  linejoin = "round",
  linemitre = 1,
  label_colour = "black",
  label_alpha = 1,
  label_parse = FALSE,
  check_overlap = FALSE,
  angle_calc = "rot",
  force_flip = TRUE,
  label_dodge = NULL,
  label_push = NULL,
  ...
)

geom_dag_edges_diagonal(
  mapping = NULL,
  data = NULL,
  position = "identity",
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  curvature = 1,
  n = 100,
  lineend = "butt",
  linejoin = "round",
  linemitre = 1,
  label_colour = "black",
  label_alpha = 1,
  label_parse = FALSE,
  check_overlap = FALSE,
  angle_calc = "rot",
  force_flip = TRUE,
  label_dodge = NULL,
  label_push = NULL,
  ...
)

geom_dag_edges_fan(
  mapping = NULL,
  data = NULL,
  position = "identity",
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  spread = 0.7,
  n = 100,
  lineend = "butt",
  linejoin = "round",
  linemitre = 1,
  label_colour = "black",
  label_alpha = 1,
  label_parse = FALSE,
  check_overlap = FALSE,
  angle_calc = "rot",
  force_flip = TRUE,
  label_dodge = NULL,
  label_push = NULL,
  ...
)
geom_dag_edges_link(
  mapping = NULL,
  data = NULL,
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

geom_dag_edges_arc(
  mapping = NULL,
  data = NULL,
  curvature = 0.5,
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  fold = FALSE,
  n = 100,
  lineend = "butt",
  linejoin = "round",
  linemitre = 1,
  label_colour = "black",
  label_alpha = 1,
  label_parse = FALSE,
  check_overlap = FALSE,
  angle_calc = "rot",
  force_flip = TRUE,
  label_dodge = NULL,
  label_push = NULL,
  ...
)

geom_dag_edges_diagonal(
  mapping = NULL,
  data = NULL,
  position = "identity",
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  curvature = 1,
  n = 100,
  lineend = "butt",
  linejoin = "round",
  linemitre = 1,
  label_colour = "black",
  label_alpha = 1,
  label_parse = FALSE,
  check_overlap = FALSE,
  angle_calc = "rot",
  force_flip = TRUE,
  label_dodge = NULL,
  label_push = NULL,
  ...
)

geom_dag_edges_fan(
  mapping = NULL,
  data = NULL,
  position = "identity",
  arrow = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  spread = 0.7,
  n = 100,
  lineend = "butt",
  linejoin = "round",
  linemitre = 1,
  label_colour = "black",
  label_alpha = 1,
  label_parse = FALSE,
  check_overlap = FALSE,
  angle_calc = "rot",
  force_flip = TRUE,
  label_dodge = NULL,
  label_push = NULL,
  ...
)

Arguments

`mapping`	Set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.
`arrow`	specification for arrow heads, as created by arrow()
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function.
`na.rm`	If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values
`show.legend`	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().
`...`	Other arguments passed to ggraph::geom_edge_*()
`curvature`	The bend of the curve. 1 approximates a halfcircle while 0 will give a straight line. Negative number will change the direction of the curve. Only used if layout circular = FALSE.
`fold`	Logical. Should arcs appear on the same side of the nodes despite different directions. Default to FALSE.
`n`	The number of points to create along the path.
`lineend`	Line end style (round, butt, square).
`linejoin`	Line join style (round, mitre, bevel).
`linemitre`	Line mitre limit (number greater than 1).
`label_colour`	The colour of the edge label. If `NA` it will use the colour of the edge.
`label_alpha`	The opacity of the edge label. If `NA` it will use the opacity of the edge.
`label_parse`	If `TRUE`, the labels will be parsed into expressions and displayed as described in `grDevices::plotmath()`.
`check_overlap`	If `TRUE`, text that overlaps previous text in the same layer will not be plotted. `check_overlap` happens at draw time and in the order of the data. Therefore data should be arranged by the label column before calling `geom_text()`. Note that this argument is not supported by `geom_label()`.
`angle_calc`	Either 'none', 'along', or 'across'. If 'none' the label will use the angle aesthetic of the geom. If 'along' The label will be written along the edge direction. If 'across' the label will be written across the edge direction.
`force_flip`	Logical. If `angle_calc` is either 'along' or 'across' should the label be flipped if it is on it's head. Default to `TRUE`.
`label_dodge`	A `grid::unit()` giving a fixed vertical shift to add to the label in case of `angle_calc` is either 'along' or 'across'
`label_push`	A `grid::unit()` giving a fixed horizontal shift to add to the label in case of `angle_calc` is either 'along' or 'across'
`spread`	Deprecated. Use `strength` instead.

Aesthetics

geom_dag_edges_link, geom_dag_edges_arc, geom_dag_edges_diagonal, and geom_dag_edges_fan understand the following aesthetics. Bold aesthetics are required.

x
y
xend
yend
edge_colour
edge_width
edge_linetype
edge_alpha
start_cap
end_cap
label
label_pos
label_size
angle
hjust
vjust
family
fontface
lineheight

geom_dag_edges_arc and geom_dag_edges_diagonal also require circular, but this is automatically set.

geom_dag_edges_fan requires to and from, but these are also automatically set.

Examples

library(ggplot2)
p <- dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  L ~ w1 + w2
) %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_point() +
  geom_dag_text() +
  theme_dag()

p + geom_dag_edges_link()
p + geom_dag_edges_arc()
p + geom_dag_edges_diagonal()
p + geom_dag_edges_fan()

library(ggplot2)
p <- dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  L ~ w1 + w2
) %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_point() +
  geom_dag_text() +
  theme_dag()

p + geom_dag_edges_link()
p + geom_dag_edges_arc()
p + geom_dag_edges_diagonal()
p + geom_dag_edges_fan()

DAG labels

Description

Label or otherwise retrieve labels from objects of either class tidy_dagitty or dagitty

Usage

label(x) <- value

## S3 replacement method for class 'dagitty'
label(x) <- value

## S3 replacement method for class 'tidy_dagitty'
label(x) <- value

dag_label(.tdy_dag, labels = NULL)

label(.tdy_dag)

has_labels(.tdy_dag)
label(x) <- value

## S3 replacement method for class 'dagitty'
label(x) <- value

## S3 replacement method for class 'tidy_dagitty'
label(x) <- value

dag_label(.tdy_dag, labels = NULL)

label(.tdy_dag)

has_labels(.tdy_dag)

Arguments

`x`	an object of either class `tidy_dagitty` or `dagitty`
`value`	a character vector
`.tdy_dag`	an object of class `tidy_dagitty`
`labels`	a character vector

Value

label returns the label attribute of x

Examples

labelled_dag <- dagify(y ~ z, x ~ z) %>%
  tidy_dagitty() %>%
  dag_label(labels = c("x" = "exposure", "y" = "outcome", "z" = "confounder"))

has_labels(labelled_dag)
labelled_dag <- dagify(y ~ z, x ~ z) %>%
  tidy_dagitty() %>%
  dag_label(labels = c("x" = "exposure", "y" = "outcome", "z" = "confounder"))

has_labels(labelled_dag)

Saturate or prune an existing DAG

Description

dag_saturate() takes a tidy DAG object and, optionally using existing coordinates, saturates the DAG based on time ordering of the nodes. To create a saturated DAG from scratch, see as_tidy_dagitty.list(). dag_prune() takes an existing DAG and removes edges. This is most useful when used together with saturated DAG.

Usage

dag_saturate(
  .tdy_dag,
  use_existing_coords = FALSE,
  layout = "time_ordered",
  seed = NULL,
  ...
)

dag_prune(.tdy_dag, edges)
dag_saturate(
  .tdy_dag,
  use_existing_coords = FALSE,
  layout = "time_ordered",
  seed = NULL,
  ...
)

dag_prune(.tdy_dag, edges)

Arguments

`.tdy_dag`	A tidy DAG object.
`use_existing_coords`	Logical, indicating whether to use existing node coordinates.
`layout`	a layout available in `ggraph`. See `ggraph::create_layout()` for details. Alternatively, `"time_ordered"` will use `time_ordered_coords()` to algorithmically sort the graph by time.
`seed`	a numeric seed for reproducible layout generation
`...`	optional arguments passed to `ggraph::create_layout()`
`edges`	A named character vector where the name is the starting node and the value is the end node, e.g. `c("x" = "y")` will remove the edge going from `x` to `y`.

Value

A tidy_dagitty object

Examples

# Example usage:
dag <- dagify(y ~ x, x ~ z)
saturated_dag <- dag_saturate(dag)

saturated_dag %>%
  ggdag(edge_type = "arc")

saturated_dag %>%
  dag_prune(c("x" = "y")) %>%
  ggdag(edge_type = "arc")
# Example usage:
dag <- dagify(y ~ x, x ~ z)
saturated_dag <- dag_saturate(dag)

saturated_dag %>%
  ggdag(edge_type = "arc")

saturated_dag %>%
  dag_prune(c("x" = "y")) %>%
  ggdag(edge_type = "arc")

Create a dagitty DAG using R-like syntax

Description

dagify() creates dagitty DAGs using a more R-like syntax. It currently accepts formulas in the usual R style, e.g. y ~ x + z, which gets translated to ⁠y <- {x z}⁠, as well as using a double tilde (⁠~~⁠) to graph bidirected variables, e.g. x1 ~~ x2 is translated to ⁠x1 <-> x2⁠.

Usage

dagify(
  ...,
  exposure = NULL,
  outcome = NULL,
  latent = NULL,
  labels = NULL,
  coords = NULL
)
dagify(
  ...,
  exposure = NULL,
  outcome = NULL,
  latent = NULL,
  labels = NULL,
  coords = NULL
)

Arguments

`...`	formulas, which are converted to `dagitty` syntax
`exposure`	a character vector for the exposure (must be a variable name in the DAG)
`outcome`	a character vector for the outcome (must be a variable name in the DAG)
`latent`	a character vector for any latent variables (must be a variable name in the DAG)
`labels`	a named character vector, labels for variables in the DAG
`coords`	coordinates for the DAG nodes. Can be a named list or a `data.frame` with columns x, y, and name

Value

a dagitty DAG

Examples


dagify(y ~ x + z, x ~ z)

coords <- list(
  x = c(A = 1, B = 2, D = 3, C = 3, F = 3, E = 4, G = 5, H = 5, I = 5),
  y = c(A = 0, B = 0, D = 1, C = 0, F = -1, E = 0, G = 1, H = 0, I = -1)
)

dag <- dagify(
  G ~ ~H,
  G ~ ~I,
  I ~ ~G,
  H ~ ~I,
  D ~ B,
  C ~ B,
  I ~ C + F,
  F ~ B,
  B ~ A,
  H ~ E,
  C ~ E + G,
  G ~ D,
  coords = coords
)

dagitty::is.dagitty(dag)

ggdag(dag)

dag2 <- dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  w1 ~ ~w2,
  exposure = "x",
  outcome = "y"
)

ggdag(dag2)

dagify(y ~ x + z, x ~ z)

coords <- list(
  x = c(A = 1, B = 2, D = 3, C = 3, F = 3, E = 4, G = 5, H = 5, I = 5),
  y = c(A = 0, B = 0, D = 1, C = 0, F = -1, E = 0, G = 1, H = 0, I = -1)
)

dag <- dagify(
  G ~ ~H,
  G ~ ~I,
  I ~ ~G,
  H ~ ~I,
  D ~ B,
  C ~ B,
  I ~ C + F,
  F ~ B,
  B ~ A,
  H ~ E,
  C ~ E + G,
  G ~ D,
  coords = coords
)

dagitty::is.dagitty(dag)

ggdag(dag)

dag2 <- dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  w1 ~ ~w2,
  exposure = "x",
  outcome = "y"
)

ggdag(dag2)

Dplyr verb methods for `tidy_dagitty` objects

Description

Dplyr verb methods for tidy_dagitty objects.

Usage

## S3 method for class 'tidy_dagitty'
select(.data, ...)

## S3 method for class 'tidy_dagitty'
filter(.data, ...)

## S3 method for class 'tidy_dagitty'
mutate(.data, ...)

## S3 method for class 'tidy_dagitty'
summarise(.data, ...)

## S3 method for class 'tidy_dagitty'
distinct(.data, ..., .keep_all = FALSE)

## S3 method for class 'tidy_dagitty'
arrange(.data, ...)

## S3 method for class 'tidy_dagitty'
group_by(.data, ...)

## S3 method for class 'tidy_dagitty'
ungroup(x, ...)

## S3 method for class 'tidy_dagitty'
transmute(.data, ...)

## S3 method for class 'tidy_dagitty'
distinct(.data, ..., .keep_all = FALSE)

## S3 method for class 'tidy_dagitty'
full_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
inner_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
left_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
right_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
anti_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'tidy_dagitty'
semi_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'tidy_dagitty'
slice(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
select_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
filter_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
mutate_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
summarise_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
arrange_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
slice_(.data, ..., .dots = list())
## S3 method for class 'tidy_dagitty'
select(.data, ...)

## S3 method for class 'tidy_dagitty'
filter(.data, ...)

## S3 method for class 'tidy_dagitty'
mutate(.data, ...)

## S3 method for class 'tidy_dagitty'
summarise(.data, ...)

## S3 method for class 'tidy_dagitty'
distinct(.data, ..., .keep_all = FALSE)

## S3 method for class 'tidy_dagitty'
arrange(.data, ...)

## S3 method for class 'tidy_dagitty'
group_by(.data, ...)

## S3 method for class 'tidy_dagitty'
ungroup(x, ...)

## S3 method for class 'tidy_dagitty'
transmute(.data, ...)

## S3 method for class 'tidy_dagitty'
distinct(.data, ..., .keep_all = FALSE)

## S3 method for class 'tidy_dagitty'
full_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
inner_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
left_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
right_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

## S3 method for class 'tidy_dagitty'
anti_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'tidy_dagitty'
semi_join(x, y, by = NULL, copy = FALSE, ...)

## S3 method for class 'tidy_dagitty'
slice(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
select_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
filter_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
mutate_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
summarise_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
arrange_(.data, ..., .dots = list())

## S3 method for class 'tidy_dagitty'
slice_(.data, ..., .dots = list())

Arguments

`.data`	data object of class `tidy_dagitty`
`...`	other arguments passed to the `dplyr` function
`.dots`, `x`, `y`, `by`, `copy`, `suffix`, `.keep_all`	see corresponding function in package `dplyr`

Examples

library(dplyr)
tidy_dagitty(m_bias()) %>%
  group_by(name) %>%
  summarize(n = n())
library(dplyr)
tidy_dagitty(m_bias()) %>%
  group_by(name) %>%
  summarize(n = n())

Generating Equivalent Models

Description

Returns a set of complete partially directed acyclic graphs (CPDAGs) given an input DAG. CPDAGs are Markov equivalent to the input graph. See dagitty::equivalentDAGs() for details. node_equivalent_dags() returns a set of DAGs, while node_equivalent_class() tags reversable edges. ggdag_equivalent_dags() plots all equivalent DAGs, while ggdag_equivalent_class() plots all reversable edges as undirected.

Usage

node_equivalent_dags(.dag, n = 100, layout = "auto", ...)

ggdag_equivalent_dags(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)

node_equivalent_class(.dag, layout = "auto")

ggdag_equivalent_class(
  .tdy_dag,
  ...,
  size = 1,
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)
node_equivalent_dags(.dag, n = 100, layout = "auto", ...)

ggdag_equivalent_dags(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)

node_equivalent_class(.dag, layout = "auto")

ggdag_equivalent_class(
  .tdy_dag,
  ...,
  size = 1,
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

Arguments

`.dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`n`	maximal number of returned graphs.
`layout`	a layout available in `ggraph`. See `ggraph::create_layout()` for details. Alternatively, `"time_ordered"` will use `time_ordered_coords()` to algorithmically sort the graph by time.
`...`	optional arguments passed to `ggraph::create_layout()`
`.tdy_dag`	an object of class `tidy_dagitty` or `dagitty`
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a tidy_dagitty with at least one DAG, including a dag column to identify graph set for equivalent DAGs or a reversable column for equivalent classes, or a ggplot

Examples

g_ex <- dagify(y ~ x + z, x ~ z)

g_ex %>% node_equivalent_class()

g_ex %>% ggdag_equivalent_dags()

g_ex <- dagify(y ~ x + z, x ~ z)

g_ex %>% node_equivalent_class()

g_ex %>% ggdag_equivalent_dags()

Find Exogenous Variables

Description

node_exogenous tags exogenous variables given an exposure and outcome. ggdag_exogenous plots all exogenous variables. See dagitty::exogenousVariables() for details.

Usage

node_exogenous(.dag, ...)

ggdag_exogenous(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)
node_exogenous(.dag, ...)

ggdag_exogenous(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)

Arguments

`.dag`, `.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`...`	additional arguments passed to `tidy_dagitty()`
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a tidy_dagitty with an exogenous column for exogenous variables or a ggplot

Examples

dag <- dagify(y ~ x1 + x2 + x3, b ~ x1 + x2)
ggdag_exogenous(dag)
node_exogenous(dag)

dag <- dagify(y ~ x1 + x2 + x3, b ~ x1 + x2)
ggdag_exogenous(dag)
node_exogenous(dag)

Quickly scale the size of a ggplot

Description

expand_plot() is a convenience function that expands the scales of a ggplot, as the large node sizes in a DAG will often get clipped in themes that don't have DAGs in mind.

Usage

expand_plot(
  expand_x = expansion(c(0.1, 0.1)),
  expand_y = expansion(c(0.1, 0.1))
)
expand_plot(
  expand_x = expansion(c(0.1, 0.1)),
  expand_y = expansion(c(0.1, 0.1))
)

Arguments

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.

Fortify a `tidy_dagitty` object for `ggplot2`

Description

Fortify a tidy_dagitty object for ggplot2

Usage

## S3 method for class 'tidy_dagitty'
fortify(model, data = NULL, ...)

## S3 method for class 'dagitty'
fortify(model, data = NULL, ...)
## S3 method for class 'tidy_dagitty'
fortify(model, data = NULL, ...)

## S3 method for class 'dagitty'
fortify(model, data = NULL, ...)

Arguments

`model`	an object of class `tidy_dagitty` or `dagitty`
`data`	(not used)
`...`	(not used)

Add common DAG layers to a ggplot

Description

geom_dag() is a helper function that adds common DAG layers to a ggplot. The purpose of geom_dag() is to simplify making custom DAGs. Most custom DAGs need the same basic layers, and so this function greatly reduces typing. It is not a true geom in that it adds many types of geoms to the plot (by default, edges, nodes, and text). While the underlying layers, all available in ggdag, are true geoms, we usually need a consistent set of layers to make a DAG. geom_dag() provides this. Because geom_dag() is not a true geom, you'll find that it is awkward for sophisticated customization. When you hit that point, you should use the underlying geoms directly.

Usage

geom_dag(
  data = 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 = 8,
  arrow_length = 5,
  use_edges = TRUE,
  use_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = FALSE,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated()
)
geom_dag(
  data = 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 = 8,
  arrow_length = 5,
  use_edges = TRUE,
  use_nodes = TRUE,
  use_stylized = FALSE,
  use_text = TRUE,
  use_labels = FALSE,
  label = NULL,
  text = NULL,
  node = deprecated(),
  stylized = deprecated()
)

Arguments

`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`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 `⁠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 `geom_dag_label_repel()`?
`label`	The bare name of a column to use for `geom_dag_label_repel()`. 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`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

A list of ggplot2 layer elements

Examples

# Basic usage with ggdag
library(ggplot2)
dag <- dagify(y ~ x, z ~ y)
ggplot(dag, aes_dag()) +
  geom_dag()
ggplot(dag, aes_dag()) +
  geom_dag(size = 1.5)
ggplot(dag, aes_dag()) +
  geom_dag(size = 1.5, text_size = 8)

# Basic usage with ggdag
library(ggplot2)
dag <- dagify(y ~ x, z ~ y)
ggplot(dag, aes_dag()) +
  geom_dag()
ggplot(dag, aes_dag()) +
  geom_dag(size = 1.5)
ggplot(dag, aes_dag()) +
  geom_dag(size = 1.5, text_size = 8)

Edges for paths activated by stratification on colliders

Description

Adjusting for a collider activates pathways between the parent of the collider. This geom adds a curved edge between any such parent nodes.

Usage

geom_dag_collider_edges(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  linewidth = 0.6,
  size = NULL,
  curvature = 0.5,
  angle = 90,
  ncp = 5,
  arrow = NULL,
  lineend = "butt",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_dag_collider_edges(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  linewidth = 0.6,
  size = NULL,
  curvature = 0.5,
  angle = 90,
  ncp = 5,
  arrow = NULL,
  lineend = "butt",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()`. If specified and `inherit.aes = TRUE` (the default), it is combined with the default mapping at the top level of the plot. You must supply `mapping` if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`stat`	The statistical transformation to use on the data for this layer, either as a `ggproto` `Geom` subclass or as a string naming the stat stripped of the `stat_` prefix (e.g. `"count"` rather than `"stat_count"`)
`position`	Position adjustment, either as a string naming the adjustment (e.g. `"jitter"` to use `position_jitter`), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
`...`	Other arguments passed on to `layer()`. These are often aesthetics, used to set an aesthetic to a fixed value, like `colour = "red"` or `size = 3`. They may also be parameters to the paired geom/stat.
`linewidth`	a numeric vector of length 1. Edge width
`size`	deprecated. Please use `linewidth`.
`curvature`	A numeric value giving the amount of curvature. Negative values produce left-hand curves, positive values produce right-hand curves, and zero produces a straight line.
`angle`	A numeric value between 0 and 180, giving an amount to skew the control points of the curve. Values less than 90 skew the curve towards the start point and values greater than 90 skew the curve towards the end point.
`ncp`	The number of control points used to draw the curve. More control points creates a smoother curve.
`arrow`	specification for arrow heads, as created by `grid::arrow()`.
`lineend`	Line end style (round, butt, square).
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders()`.

Examples

library(dagitty)
library(ggplot2)
dagify(m ~ a + b, x ~ a, y ~ b) %>%
  tidy_dagitty() %>%
  control_for("m") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_point() +
  geom_dag_text() +
  theme_dag() +
  scale_adjusted()
library(dagitty)
library(ggplot2)
dagify(m ~ a + b, x ~ a, y ~ b) %>%
  tidy_dagitty() %>%
  control_for("m") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend, shape = adjusted)) +
  geom_dag_edges() +
  geom_dag_collider_edges() +
  geom_dag_point() +
  geom_dag_text() +
  theme_dag() +
  scale_adjusted()

Directed and bidirected DAG edges

Description

Directed and bidirected DAG edges

Usage

geom_dag_edges(
  mapping = NULL,
  data_directed = filter_direction("->"),
  data_bidirected = filter_direction("<->"),
  curvature = 0.3,
  arrow_directed = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  arrow_bidirected = grid::arrow(length = grid::unit(5, "pt"), ends = "both", type =
    "closed"),
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  fold = FALSE,
  ...
)
geom_dag_edges(
  mapping = NULL,
  data_directed = filter_direction("->"),
  data_bidirected = filter_direction("<->"),
  curvature = 0.3,
  arrow_directed = grid::arrow(length = grid::unit(5, "pt"), type = "closed"),
  arrow_bidirected = grid::arrow(length = grid::unit(5, "pt"), ends = "both", type =
    "closed"),
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  fold = FALSE,
  ...
)

Arguments

`mapping`	Set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
`data_directed`, `data_bidirected`	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.
`curvature`	The bend of the curve. 1 approximates a halfcircle while 0 will give a straight line. Negative number will change the direction of the curve. Only used if layout circular = FALSE.
`arrow_directed`, `arrow_bidirected`	specification for arrow heads, as created by arrow()
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function.
`na.rm`	If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values
`show.legend`	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().
`fold`	Logical. Should arcs appear on the same side of the nodes despite different directions. Default to FALSE.
`...`	Other arguments passed to ggraph::geom_edge_*()

Aesthetics

geom_dag_edges understand the following aesthetics. Bold aesthetics are required.

x
y
xend
yend
edge_colour
edge_width
edge_linetype
edge_alpha
start_cap
end_cap
label
label_pos
label_size
angle
hjust
vjust
family
fontface
lineheight

geom_dag_edges also uses geom_dag_edges_arc, which requires the circular aesthetic, but this is automatically set.

Examples

library(ggplot2)
dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  w1 ~ ~w2
) %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text() +
  theme_dag()

library(ggplot2)
dagify(
  y ~ x + z2 + w2 + w1,
  x ~ z1 + w1,
  z1 ~ w1 + v,
  z2 ~ w2 + v,
  w1 ~ ~w2
) %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text() +
  theme_dag()

Node text labels

Description

Node text labels

Usage

geom_dag_label(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  parse = FALSE,
  nudge_x = 0,
  nudge_y = 0,
  check_overlap = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_dag_label(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  parse = FALSE,
  nudge_x = 0,
  nudge_y = 0,
  check_overlap = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()`. If specified and `inherit.aes = TRUE` (the default), it is combined with the default mapping at the top level of the plot. You must supply `mapping` if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`stat`	The statistical transformation to use on the data for this layer, either as a `ggproto` `Geom` subclass or as a string naming the stat stripped of the `stat_` prefix (e.g. `"count"` rather than `"stat_count"`)
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function. Cannot be jointly specified with `nudge_x` or `nudge_y`.
`...`	Other arguments passed on to `layer()`. These are often aesthetics, used to set an aesthetic to a fixed value, like `colour = "red"` or `size = 3`. They may also be parameters to the paired geom/stat.
`parse`	If `TRUE`, the labels will be parsed into expressions and displayed as described in `?plotmath`.
`nudge_x`, `nudge_y`	Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with `position`.
`check_overlap`	If `TRUE`, text that overlaps previous text in the same layer will not be plotted. `check_overlap` happens at draw time and in the order of the data. Therefore data should be arranged by the label column before calling `geom_text()`. Note that this argument is not supported by `geom_label()`.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders()`.

Aesthetics

geom_dag_label understand the following aesthetics (required aesthetics are in bold):

x
y
label
alpha
angle
colour
family
fontface
group
hjust
lineheight
size
vjust

Examples

library(ggplot2)
library(ggraph)
g <- dagify(m ~ x + y, y ~ x)

ggdag(g, text = FALSE) + geom_dag_label()

g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges(aes(
    start_cap = label_rect(name, padding = margin(2.5, 2.5, 2.5, 2.5, "mm")),
    end_cap = label_rect(name, padding = margin(2.5, 2.5, 2.5, 2.5, "mm"))
  )) +
  geom_dag_label(size = 5, fill = "black", color = "white") +
  theme_dag()
library(ggplot2)
library(ggraph)
g <- dagify(m ~ x + y, y ~ x)

ggdag(g, text = FALSE) + geom_dag_label()

g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges(aes(
    start_cap = label_rect(name, padding = margin(2.5, 2.5, 2.5, 2.5, "mm")),
    end_cap = label_rect(name, padding = margin(2.5, 2.5, 2.5, 2.5, "mm"))
  )) +
  geom_dag_label(size = 5, fill = "black", color = "white") +
  theme_dag()

Node text

Description

Node text

Usage

geom_dag_text(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  parse = FALSE,
  nudge_x = 0,
  nudge_y = 0,
  check_overlap = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_dag_text(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  parse = FALSE,
  nudge_x = 0,
  nudge_y = 0,
  check_overlap = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()`. If specified and `inherit.aes = TRUE` (the default), it is combined with the default mapping at the top level of the plot. You must supply `mapping` if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`stat`	The statistical transformation to use on the data for this layer, either as a `ggproto` `Geom` subclass or as a string naming the stat stripped of the `stat_` prefix (e.g. `"count"` rather than `"stat_count"`)
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function. Cannot be jointly specified with `nudge_x` or `nudge_y`.
`...`	Other arguments passed on to `layer()`. These are often aesthetics, used to set an aesthetic to a fixed value, like `colour = "red"` or `size = 3`. They may also be parameters to the paired geom/stat.
`parse`	If `TRUE`, the labels will be parsed into expressions and displayed as described in `?plotmath`.
`nudge_x`, `nudge_y`	Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with `position`.
`check_overlap`	If `TRUE`, text that overlaps previous text in the same layer will not be plotted. `check_overlap` happens at draw time and in the order of the data. Therefore data should be arranged by the label column before calling `geom_text()`. Note that this argument is not supported by `geom_label()`.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders()`.

Aesthetics

geom_dag_text understand the following aesthetics (required aesthetics are in bold):

x
y
label
alpha
angle
colour
family
fontface
group
hjust
lineheight
size
vjust

Examples

library(ggplot2)
g <- dagify(m ~ x + y, y ~ x)
g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_point() +
  geom_dag_edges() +
  geom_dag_text() +
  theme_dag()
library(ggplot2)
g <- dagify(m ~ x + y, y ~ x)
g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_point() +
  geom_dag_edges() +
  geom_dag_text() +
  theme_dag()

Quickly plot a DAG in ggplot2

Description

ggdag() is a wrapper to quickly plot DAGs.

Usage

ggdag(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)
ggdag(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)

Arguments

`.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`...`	additional arguments passed to `tidy_dagitty()`
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a ggplot

Examples


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

ggdag(dag)
ggdag(dag) + theme_dag()

ggdag(dagitty::randomDAG(5, .5))

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

ggdag(dag)
ggdag(dag) + theme_dag()

ggdag(dagitty::randomDAG(5, .5))

Quickly plot a DAG in ggplot2

Description

ggdag_classic() is a wrapper to quickly plot DAGs in a more traditional style.

Usage

ggdag_classic(
  .tdy_dag,
  ...,
  size = 8,
  label_rect_size = NULL,
  text_label = "name",
  text_col = "black"
)
ggdag_classic(
  .tdy_dag,
  ...,
  size = 8,
  label_rect_size = NULL,
  text_label = "name",
  text_col = "black"
)

Arguments

`.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`...`	additional arguments passed to `tidy_dagitty()`
`size`	text size, with a default of 8.
`label_rect_size`	specify the `fontsize` argument in `ggraph::label_rect`; default is `NULL`, in which case it is scaled relative ti `size`
`text_label`	text variable, with a default of "name"
`text_col`	text color, with a default of "black"

Value

a ggplot

Examples


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

ggdag_classic(dag)
ggdag_classic(dag) + theme_dag_blank()

ggdag_classic(dagitty::randomDAG(5, .5))

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

ggdag_classic(dag)
ggdag_classic(dag) + theme_dag_blank()

ggdag_classic(dagitty::randomDAG(5, .5))

Create a new ggplot

Description

Create a new ggplot

Usage

## S3 method for class 'tidy_dagitty'
ggplot(data = NULL, mapping = aes(), ...)

## S3 method for class 'dagitty'
ggplot(data = NULL, mapping = aes(), ...)
## S3 method for class 'tidy_dagitty'
ggplot(data = NULL, mapping = aes(), ...)

## S3 method for class 'dagitty'
ggplot(data = NULL, mapping = aes(), ...)

Arguments

`data`	Default dataset to use for plot. If not already a data.frame, will be converted to one by `fortify()`. If not specified, must be supplied in each layer added to the plot.
`mapping`	Default list of aesthetic mappings to use for plot. If not specified, must be supplied in each layer added to the plot.
`...`	Other arguments passed on to methods. Not currently used.

Repulsive textual annotations

Description

These functions are minor modifications of those in the ggrepel package. geom_dag_text_repel() adds text directly to the plot. geom_dag_label_repel() draws a rectangle underneath the text, making it easier to read. The text labels repel away from each other and away from the data points. geom_dag_label_repel2() is a slightly stylized version of geom_dag_label_repel()' that often looks better on DAGs.

Usage

geom_dag_text_repel(
  mapping = NULL,
  data = NULL,
  parse = FALSE,
  ...,
  box.padding = 1.25,
  point.padding = 1.5,
  segment.color = "#666666",
  fontface = "bold",
  segment.size = 0.5,
  arrow = NULL,
  force = 1,
  max.iter = 2000,
  nudge_x = 0,
  nudge_y = 0,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_dag_label_repel(
  mapping = NULL,
  data = NULL,
  parse = FALSE,
  ...,
  box.padding = grid::unit(1.25, "lines"),
  label.padding = grid::unit(0.25, "lines"),
  point.padding = grid::unit(1.5, "lines"),
  label.r = grid::unit(0.15, "lines"),
  label.size = 0.25,
  segment.color = "grey50",
  segment.size = 0.5,
  arrow = NULL,
  force = 1,
  max.iter = 2000,
  nudge_x = 0,
  nudge_y = 0,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_dag_label_repel2(
  mapping = NULL,
  data = NULL,
  box.padding = 2,
  max.overlaps = Inf,
  label.size = NA,
  ...
)
geom_dag_text_repel(
  mapping = NULL,
  data = NULL,
  parse = FALSE,
  ...,
  box.padding = 1.25,
  point.padding = 1.5,
  segment.color = "#666666",
  fontface = "bold",
  segment.size = 0.5,
  arrow = NULL,
  force = 1,
  max.iter = 2000,
  nudge_x = 0,
  nudge_y = 0,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_dag_label_repel(
  mapping = NULL,
  data = NULL,
  parse = FALSE,
  ...,
  box.padding = grid::unit(1.25, "lines"),
  label.padding = grid::unit(0.25, "lines"),
  point.padding = grid::unit(1.5, "lines"),
  label.r = grid::unit(0.15, "lines"),
  label.size = 0.25,
  segment.color = "grey50",
  segment.size = 0.5,
  arrow = NULL,
  force = 1,
  max.iter = 2000,
  nudge_x = 0,
  nudge_y = 0,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_dag_label_repel2(
  mapping = NULL,
  data = NULL,
  box.padding = 2,
  max.overlaps = Inf,
  label.size = NA,
  ...
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes` or `aes_`. If specified and `inherit.aes = TRUE` (the default), is combined with the default mapping at the top level of the plot. You only need to supply `mapping` if there isn't a mapping defined for the plot.
`data`	A data frame. If specified, overrides the default data frame defined at the top level of the plot.
`parse`	If TRUE, the labels will be parsed into expressions and displayed as described in ?plotmath
`...`	other arguments passed on to `layer`. There are three types of arguments you can use here: Aesthetics: to set an aesthetic to a fixed value, like `colour = "red"` or `size = 3`. Other arguments to the layer, for example you override the default `stat` associated with the layer. Other arguments passed on to the stat.
`box.padding`	Amount of padding around bounding box, as unit or number. Defaults to 0.25. (Default unit is lines, but other units can be specified by passing `unit(x, "units")`).
`point.padding`	Amount of padding around labeled point, as unit or number. Defaults to 0. (Default unit is lines, but other units can be specified by passing `unit(x, "units")`).
`segment.color`, `segment.size`	See `ggrepel::geom_text_repel()`
`fontface`	A character vector. Default is "bold"
`arrow`	specification for arrow heads, as created by `arrow`
`force`	Force of repulsion between overlapping text labels. Defaults to 1.
`max.iter`	Maximum number of iterations to try to resolve overlaps. Defaults to 10000.
`nudge_x`, `nudge_y`	Horizontal and vertical adjustments to nudge the starting position of each text label. The units for `nudge_x` and `nudge_y` are the same as for the data units on the x-axis and y-axis.
`na.rm`	If `FALSE` (the default), removes missing values with a warning. If `TRUE` silently removes missing values.
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders`.
`label.padding`	Amount of padding around label, as unit or number. Defaults to 0.25. (Default unit is lines, but other units can be specified by passing `unit(x, "units")`).
`label.r`	Radius of rounded corners, as unit or number. Defaults to 0.15. (Default unit is lines, but other units can be specified by passing `unit(x, "units")`).
`label.size`	Size of label border, in mm.
`max.overlaps`	Exclude text labels when they overlap too many other things. For each text label, we count how many other text labels or other data points it overlaps, and exclude the text label if it has too many overlaps. Defaults to 10.

Examples

library(ggplot2)
g <- dagify(
  m ~ x + y,
  y ~ x,
  exposure = "x",
  outcome = "y",
  latent = "m",
  labels = c("x" = "Exposure", "y" = "Outcome", "m" = "Collider")
)

g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text_repel(aes(label = name), show.legend = FALSE) +
  theme_dag()

g %>%
  tidy_dagitty() %>%
  dag_label(labels = c(
    "x" = "This is the exposure",
    "y" = "Here's the outcome",
    "m" = "Here is where they collide"
  )) %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text() +
  geom_dag_label_repel(
    aes(label = label, fill = label),
    col = "white",
    show.legend = FALSE
  ) +
  theme_dag()

library(ggplot2)
g <- dagify(
  m ~ x + y,
  y ~ x,
  exposure = "x",
  outcome = "y",
  latent = "m",
  labels = c("x" = "Exposure", "y" = "Outcome", "m" = "Collider")
)

g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text_repel(aes(label = name), show.legend = FALSE) +
  theme_dag()

g %>%
  tidy_dagitty() %>%
  dag_label(labels = c(
    "x" = "This is the exposure",
    "y" = "Here's the outcome",
    "m" = "Here is where they collide"
  )) %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  geom_dag_point() +
  geom_dag_text() +
  geom_dag_label_repel(
    aes(label = label, fill = label),
    col = "white",
    show.legend = FALSE
  ) +
  theme_dag()

Find Instrumental Variables

Description

node_instrumental tags instrumental variables given an exposure and outcome. ggdag_instrumental plots all instrumental variables. See dagitty::instrumentalVariables() for details.

Usage

node_instrumental(.dag, exposure = NULL, outcome = NULL, ...)

ggdag_instrumental(
  .tdy_dag,
  exposure = NULL,
  outcome = 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()
)
node_instrumental(.dag, exposure = NULL, outcome = NULL, ...)

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

Arguments

`.dag`, `.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`exposure`	character vector of length 1, name of exposure variable. Default is `NULL`, in which case it will check the input DAG for exposure.
`outcome`	character vector of length 1, name of exposure variable. Default is `NULL`, in which case it will check the input DAG for exposure.
`...`	additional arguments passed to `tidy_dagitty()`
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a tidy_dagitty with an instrumental column for instrumental variables or a ggplot

Examples

library(dagitty)

node_instrumental(dagitty("dag{ i->x->y; x<->y }"), "x", "y")
ggdag_instrumental(dagitty("dag{ i->x->y; i2->x->y; x<->y }"), "x", "y")

library(dagitty)

node_instrumental(dagitty("dag{ i->x->y; x<->y }"), "x", "y")
ggdag_instrumental(dagitty("dag{ i->x->y; i2->x->y; x<->y }"), "x", "y")

Assess if a variable confounds a relationship

Description

Assess if a variable confounds a relationship

Usage

is_confounder(.tdy_dag, z, x, y, direct = FALSE)
is_confounder(.tdy_dag, z, x, y, direct = FALSE)

Arguments

`.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`z`	a character vector, the potential confounder
`x`, `y`	a character vector, the variables z may confound.
`direct`	logical. Only consider direct confounding? Default is `FALSE`

Value

Logical. Is the variable a confounder?

Examples

dag <- dagify(y ~ z, x ~ z)

is_confounder(dag, "z", "x", "y")
is_confounder(dag, "x", "z", "y")

dag <- dagify(y ~ z, x ~ z)

is_confounder(dag, "z", "x", "y")
is_confounder(dag, "x", "z", "y")

Test for object class for tidy_dagitty

Description

Test for object class for tidy_dagitty

Usage

is.tidy_dagitty(x)
is.tidy_dagitty(x)

Arguments

`x`	object to be tested

DAG Nodes

Description

geom_dag_node and geom_dag_point are very similar to ggplot2::geom_point but with a few defaults changed. geom_dag_node is slightly stylized and includes an internal white circle, while geom_dag_point plots a single point.

Usage

geom_dag_node(
  mapping = NULL,
  data = NULL,
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_dag_point(
  mapping = NULL,
  data = NULL,
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_dag_node(
  mapping = NULL,
  data = NULL,
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

geom_dag_point(
  mapping = NULL,
  data = NULL,
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()`. If specified and `inherit.aes = TRUE` (the default), it is combined with the default mapping at the top level of the plot. You must supply `mapping` if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`position`	Position adjustment, either as a string naming the adjustment (e.g. `"jitter"` to use `position_jitter`), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
`...`	Other arguments passed on to `layer()`. These are often aesthetics, used to set an aesthetic to a fixed value, like `colour = "red"` or `size = 3`. They may also be parameters to the paired geom/stat.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders()`.

Aesthetics

geom_dag_node and geom_dag_point understand the following aesthetics (required aesthetics are in bold):

x
y
alpha
colour
fill
shape
size
stroke
filter

geom_dag_node also accepts:

internal_colour

Examples

library(ggplot2)
g <- dagify(m ~ x + y, y ~ x)
p <- g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  theme_dag()

p +
  geom_dag_node() +
  geom_dag_text()

p +
  geom_dag_point() +
  geom_dag_text()
library(ggplot2)
g <- dagify(m ~ x + y, y ~ x)
p <- g %>%
  tidy_dagitty() %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_edges() +
  theme_dag()

p +
  geom_dag_node() +
  geom_dag_text()

p +
  geom_dag_point() +
  geom_dag_text()

Find Open Paths Between Variables

Description

dag_paths finds open paths between a given exposure and outcome. ggdag_paths and ggdag_paths_fan plot all open paths. See dagitty::paths() for details.

Usage

dag_paths(
  .dag,
  from = NULL,
  to = NULL,
  adjust_for = NULL,
  limit = 100,
  directed = FALSE,
  paths_only = FALSE,
  ...
)

ggdag_paths(
  .tdy_dag,
  from = NULL,
  to = NULL,
  adjust_for = NULL,
  limit = 100,
  directed = FALSE,
  shadow = TRUE,
  ...,
  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 = 8,
  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()
)

ggdag_paths_fan(
  .tdy_dag,
  from = NULL,
  to = NULL,
  adjust_for = NULL,
  limit = 100,
  directed = FALSE,
  ...,
  shadow = TRUE,
  spread = 0.7,
  size = 1,
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)
dag_paths(
  .dag,
  from = NULL,
  to = NULL,
  adjust_for = NULL,
  limit = 100,
  directed = FALSE,
  paths_only = FALSE,
  ...
)

ggdag_paths(
  .tdy_dag,
  from = NULL,
  to = NULL,
  adjust_for = NULL,
  limit = 100,
  directed = FALSE,
  shadow = TRUE,
  ...,
  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 = 8,
  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()
)

ggdag_paths_fan(
  .tdy_dag,
  from = NULL,
  to = NULL,
  adjust_for = NULL,
  limit = 100,
  directed = FALSE,
  ...,
  shadow = TRUE,
  spread = 0.7,
  size = 1,
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

Arguments

`.dag`, `.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`from`	character vector of length 1, name of exposure variable. Default is `NULL`, in which case it will check the input DAG for exposure.
`to`	character vector of length 1, name of exposure variable. Default is `NULL`, in which case it will check the input DAG for exposure.
`adjust_for`	character vector, a set of variables to control for. Default is `NULL`.
`limit`	maximum amount of paths to show. In general, the number of paths grows exponentially with the number of variables in the graph, such that path inspection is not useful except for the most simple models.
`directed`	logical. Should only directed paths be shown?
`paths_only`	logical. Should only open paths be returned? Default is `FALSE`, which includes every variable and edge in the DAG regardless if they are part of the path.
`...`	additional arguments passed to `tidy_dagitty()`
`shadow`	logical. Show edges which are not on an open path?
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.
`spread`	the width of the fan spread

Value

a tidy_dagitty with a path column for path variables and a set grouping column or a ggplot.

Examples

confounder_triangle(x_y_associated = TRUE) %>%
  dag_paths(from = "x", to = "y")

confounder_triangle(x_y_associated = TRUE) %>%
  ggdag_paths(from = "x", to = "y")

butterfly_bias(x_y_associated = TRUE) %>%
  ggdag_paths_fan(shadow = TRUE)

confounder_triangle(x_y_associated = TRUE) %>%
  dag_paths(from = "x", to = "y")

confounder_triangle(x_y_associated = TRUE) %>%
  ggdag_paths(from = "x", to = "y")

butterfly_bias(x_y_associated = TRUE) %>%
  ggdag_paths_fan(shadow = TRUE)

Print a `tidy_dagitty`

Description

Print a tidy_dagitty

Usage

## S3 method for class 'tidy_dagitty'
print(x, ...)
## S3 method for class 'tidy_dagitty'
print(x, ...)

Arguments

`x`	an object of class `tidy_dagitty`
`...`	optional arguments passed to `print()`

Pull components from DAG objects

Description

pull_dag() and pull_dag_data() are generic methods to pull components of DAG objects, e.g. tidy_dagitty, such as the dagitty object or the data frame associated with it. These methods are recommended over extracting components manually, e.g. my_dag$data, because the internal structure of these objects may change over time. Similarly, use update_dag() if you want to sync the data back to the DAG object or override it with another DAG; use update_dag_data() to do update the data frame. This is useful with pull_dag_data().

Usage

pull_dag(x, ...)

## S3 method for class 'tidy_dagitty'
pull_dag(x, ...)

## S3 method for class 'dagitty'
pull_dag(x, ...)

pull_dag_data(x, ...)

## S3 method for class 'tidy_dagitty'
pull_dag_data(x, ...)

## S3 method for class 'dagitty'
pull_dag_data(x, ...)

update_dag_data(x) <- value

## S3 replacement method for class 'tidy_dagitty'
update_dag_data(x) <- value

update_dag(x, ...)

update_dag(x) <- value

## S3 method for class 'tidy_dagitty'
update_dag(x, ...)

## S3 replacement method for class 'tidy_dagitty'
update_dag(x) <- value
pull_dag(x, ...)

## S3 method for class 'tidy_dagitty'
pull_dag(x, ...)

## S3 method for class 'dagitty'
pull_dag(x, ...)

pull_dag_data(x, ...)

## S3 method for class 'tidy_dagitty'
pull_dag_data(x, ...)

## S3 method for class 'dagitty'
pull_dag_data(x, ...)

update_dag_data(x) <- value

## S3 replacement method for class 'tidy_dagitty'
update_dag_data(x) <- value

update_dag(x, ...)

update_dag(x) <- value

## S3 method for class 'tidy_dagitty'
update_dag(x, ...)

## S3 replacement method for class 'tidy_dagitty'
update_dag(x) <- value

Arguments

`x`	a `tidy_dagitty` or `dagitty` object.
`...`	For `dagitty` objects, passed to `tidy_dagitty()` if needed, otherwise currently unused.
`value`	a value to set, either a `dagitty` or `data.frame` object, depending on the function.

Value

a DAG object, e.g. dagitty, or data frame

Examples


tidy_dagitty_obj <- dagify(y ~ x + z, x ~ z) %>%
  tidy_dagitty()
dag <- pull_dag(tidy_dagitty_obj)
dag_data <- pull_dag_data(tidy_dagitty_obj)

tidy_dagitty_obj %>%
  dplyr::mutate(name = toupper(name)) %>%
  # recreate the DAG component
  update_dag()

dag_data$label <- paste0(dag_data$name, "(observed)")
update_dag_data(tidy_dagitty_obj) <- dag_data

tidy_dagitty_obj <- dagify(y ~ x + z, x ~ z) %>%
  tidy_dagitty()
dag <- pull_dag(tidy_dagitty_obj)
dag_data <- pull_dag_data(tidy_dagitty_obj)

tidy_dagitty_obj %>%
  dplyr::mutate(name = toupper(name)) %>%
  # recreate the DAG component
  update_dag()

dag_data$label <- paste0(dag_data$name, "(observed)")
update_dag_data(tidy_dagitty_obj) <- dag_data

Query and Test Conditional Independence in a DAG

Description

query_conditional_independence() queries conditional independencies implied by a given DAG. These serve as potential robustness checks for your DAG. test_conditional_independence() runs the tests of independence implied by the DAG on a given dataset. ggdag_conditional_independence() plots the results as a forest plot.

Usage

query_conditional_independence(
  .tdy_dag,
  type = "missing.edge",
  max.results = Inf
)

test_conditional_independence(
  .tdy_dag,
  data = NULL,
  type = c("cis", "cis.loess", "cis.chisq", "cis.pillai", "tetrads", "tetrads.within",
    "tetrads.between", "tetrads.epistemic"),
  tests = NULL,
  sample.cov = NULL,
  sample.nobs = NULL,
  conf.level = 0.95,
  R = NULL,
  max.conditioning.variables = NULL,
  abbreviate.names = FALSE,
  tol = NULL,
  loess.pars = NULL
)

ggdag_conditional_independence(
  .test_result,
  vline_linewidth = 0.8,
  vline_color = "grey70",
  pointrange_fatten = 3
)
query_conditional_independence(
  .tdy_dag,
  type = "missing.edge",
  max.results = Inf
)

test_conditional_independence(
  .tdy_dag,
  data = NULL,
  type = c("cis", "cis.loess", "cis.chisq", "cis.pillai", "tetrads", "tetrads.within",
    "tetrads.between", "tetrads.epistemic"),
  tests = NULL,
  sample.cov = NULL,
  sample.nobs = NULL,
  conf.level = 0.95,
  R = NULL,
  max.conditioning.variables = NULL,
  abbreviate.names = FALSE,
  tol = NULL,
  loess.pars = NULL
)

ggdag_conditional_independence(
  .test_result,
  vline_linewidth = 0.8,
  vline_color = "grey70",
  pointrange_fatten = 3
)

Arguments

`.tdy_dag`	A tidy DAG object.
`type`	can be one of "missing.edge", "basis.set", or "all.pairs". With the first, one or more minimal testable implication (with the smallest possible conditioning set) is returned per missing edge of the graph. With "basis.set", one testable implication is returned per vertex of the graph that has non-descendants other than its parents. Basis sets can be smaller, but they involve higher-dimensional independencies, whereas missing edge sets involve only independencies between two variables at a time. With "all.pairs", the function will return a list of all implied conditional independencies between two variables at a time. Beware, because this can be a very long list and it may not be feasible to compute this except for small graphs.
`max.results`	integer. The listing of conditional independencies is stopped once this many results have been found. Use `Inf` to generate them all. This applies only when `type="missing.edge"` or `type="all"`.
`data`	matrix or data frame containing the data.
`tests`	list of the precise tests to perform. If not given, the list of tests is automatically derived from the input graph. Can be used to restrict testing to only a certain subset of tests (for instance, to test only those conditional independencies for which the conditioning set is of a reasonably low dimension, such as shown in the example).
`sample.cov`	the sample covariance matrix; ignored if `data` is supplied. Either `data` or `sample.cov` and `sample.nobs` must be supplied.
`sample.nobs`	number of observations; ignored if `data` is supplied.
`conf.level`	determines the size of confidence intervals for test statistics.
`R`	how many bootstrap replicates for estimating confidence intervals. If `NULL`, then confidence intervals are based on normal approximation. For tetrads, the normal approximation is only valid in large samples even if the data are normally distributed.
`max.conditioning.variables`	for conditional independence testing, this parameter can be used to perform only those tests where the number of conditioning variables does not exceed the given value. High-dimensional conditional independence tests can be very unreliable.
`abbreviate.names`	logical. Whether to abbreviate variable names (these are used as row names in the returned data frame).
`tol`	bound value for tolerated deviation from local test value. By default, we perform a two-sided test of the hypothesis theta=0. If this parameter is given, the test changes to abs(theta)=tol versus abs(theta)>tol.
`loess.pars`	list of parameter to be passed on to `loess` (for `type="cis.loess"`), for example the smoothing range. `ciTest(X,Y,Z,data)` is a convenience function to test a single conditional independence independently of a DAG.
`.test_result`	A data frame containing the results of conditional independence tests created by `test_conditional_independence()`.
`vline_linewidth`	Line width for the vertical line indicating no effect.
`vline_color`	Color of the vertical line.
`pointrange_fatten`	Factor to fatten the point range.

Value

Either a tibble summarizing the conditional independencies in the DAG or test results, or a ggplot of the results.

Quickly create a DAGs with common structures of bias

Description

base functions create an object of class dagitty; ⁠ggdag_* ⁠ functions are wrappers that also call ggdag() on the dagitty object.

Usage

m_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE
)

butterfly_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE
)

confounder_triangle(x = NULL, y = NULL, z = NULL, x_y_associated = FALSE)

collider_triangle(x = NULL, y = NULL, m = NULL, x_y_associated = FALSE)

mediation_triangle(x = NULL, y = NULL, m = NULL, x_y_associated = FALSE)

ggdag_m_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_butterfly_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_confounder_triangle(
  x = NULL,
  y = NULL,
  z = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_collider_triangle(
  x = NULL,
  y = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_mediation_triangle(
  x = NULL,
  y = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)
m_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE
)

butterfly_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE
)

confounder_triangle(x = NULL, y = NULL, z = NULL, x_y_associated = FALSE)

collider_triangle(x = NULL, y = NULL, m = NULL, x_y_associated = FALSE)

mediation_triangle(x = NULL, y = NULL, m = NULL, x_y_associated = FALSE)

ggdag_m_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_butterfly_bias(
  x = NULL,
  y = NULL,
  a = NULL,
  b = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_confounder_triangle(
  x = NULL,
  y = NULL,
  z = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_collider_triangle(
  x = NULL,
  y = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

ggdag_mediation_triangle(
  x = NULL,
  y = NULL,
  m = NULL,
  x_y_associated = FALSE,
  size = 1,
  edge_type = "link_arc",
  node_size = 16,
  text_size = 3.88,
  label_size = text_size,
  text_col = "white",
  label_col = "black",
  edge_width = 0.6,
  edge_cap = 8,
  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()
)

Arguments

`x`, `y`, `a`, `b`, `m`, `z`	Character vector. Optional label. Default is `NULL`
`x_y_associated`	Logical. Are x and y associated? Default is `FALSE`.
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Value

a DAG of class dagitty or a ggplot

Examples

m_bias() %>% ggdag_adjust("m")
ggdag_confounder_triangle()

m_bias() %>% ggdag_adjust("m")
ggdag_confounder_triangle()

Quickly remove plot axes and grids

Description

remove_axes() and remove_grid() are convenience functions that removes the axes and grids from a ggplot, respectively. This is useful when you want to use an existing theme, e.g. those included in ggplot2, for a DAG.

Usage

remove_axes()

remove_grid()
remove_axes()

remove_grid()

Examples

library(ggplot2)
ggdag(confounder_triangle()) +
  theme_bw() +
  remove_axes()

library(ggplot2)
ggdag(confounder_triangle()) +
  theme_bw() +
  remove_axes()

Common scale adjustments for DAGs

Description

scale_adjusted() is a convenience function that implements ways of visualizing adjustment for a variable. By convention, a square shape is used to indicate adjustment and a circle when not adjusted. Arrows out of adjusted variables are often eliminated or de-emphasized, and scale_adjusted() uses a lower alpha for these arrows. When adjusting a collider, a dashed line is sometimes used to demarcate opened pathways, and scale_adjusted() does this whenever geom_dag_collider_edges() is used. scale_dag() is deprecated in favor of scale_adjusted().

Usage

scale_adjusted(include_alpha = FALSE)

scale_dag(breaks = ggplot2::waiver())
scale_adjusted(include_alpha = FALSE)

scale_dag(breaks = ggplot2::waiver())

Arguments

include_alpha

Logical. Include alpha-related scales?

breaks

One of:

NULL for no breaks
waiver() for the default breaks computed by the transformation object
A numeric vector of positions
A function that takes the limits as input and returns breaks as output

Simulate Data from Structural Equation Model

Description

This is a thin wrapper for the simulateSEM()function in dagitty that works with tidied dagitty objects. It treats the input DAG as a structural equation model, generating random path coefficients and simulating corresponding data. See dagitty::simulateSEM() for details.

Usage

simulate_data(
  .tdy_dag,
  b.default = NULL,
  b.lower = -0.6,
  b.upper = 0.6,
  eps = 1,
  N = 500,
  standardized = TRUE
)
simulate_data(
  .tdy_dag,
  b.default = NULL,
  b.lower = -0.6,
  b.upper = 0.6,
  eps = 1,
  N = 500,
  standardized = TRUE
)

Arguments

`.tdy_dag`	the input DAG, which can be a `tidy_dagitty` or `dagitty` object.
`b.default`	default path coefficient applied to arrows for which no coefficient is defined in the model syntax.
`b.lower`	lower bound for random path coefficients, applied if b.default = NULL.
`b.upper`	upper bound for path coefficients.
`eps`	residual variance (only meaningful if standardized=FALSE).
`N`	number of samples to generate.
`standardized`	whether a standardized output is desired (all variables have variance 1).

Value

a tblwith N values for each variable in .tdy_dag

Examples

dagify(y ~ z, x ~ z) %>%
  tidy_dagitty() %>%
  simulate_data()
dagify(y ~ z, x ~ z) %>%
  tidy_dagitty() %>%
  simulate_data()

Convert a `tidy_dagitty` object to tbl_df

Description

Convert a tidy_dagitty object to tbl_df

Usage

tbl_df.tidy_daggity(.tdy_dag)
tbl_df.tidy_daggity(.tdy_dag)

Arguments

.tdy_dag

an object of class tidy_dagitty

Detecting colliders in DAGs

Description

Detecting colliders in DAGs

Usage

is_collider(.dag, .var, downstream = TRUE)

is_downstream_collider(.dag, .var)
is_collider(.dag, .var, downstream = TRUE)

is_downstream_collider(.dag, .var)

Arguments

`.dag`	an input graph, an object of class `tidy_dagitty` or `dagitty`
`.var`	a character vector of length 1, the potential collider to check
`downstream`	Logical. Check for downstream colliders? Default is `TRUE`.

Value

Logical. Is the variable a collider or downstream collider?

Examples

dag <- dagify(m ~ x + y, m_jr ~ m)
is_collider(dag, "m")
is_downstream_collider(dag, "m_jr")

#  a downstream collider is also treated as a collider
is_collider(dag, "m_jr")

#  but a direct collider is not treated as a downstream collider
is_downstream_collider(dag, "m")

dag <- dagify(m ~ x + y, m_jr ~ m)
is_collider(dag, "m")
is_downstream_collider(dag, "m_jr")

#  a downstream collider is also treated as a collider
is_collider(dag, "m_jr")

#  but a direct collider is not treated as a downstream collider
is_downstream_collider(dag, "m")

Minimalist DAG themes

Description

Minimalist DAG themes

Usage

theme_dag_blank(base_size = 12, base_family = "", ...)

theme_dag(base_size = 12, base_family = "", ...)

theme_dag_grid(base_size = 12, base_family = "", ...)
theme_dag_blank(base_size = 12, base_family = "", ...)

theme_dag(base_size = 12, base_family = "", ...)

theme_dag_grid(base_size = 12, base_family = "", ...)

Arguments

`base_size`	base font size, given in pts.
`base_family`	base font family
`...`	additional arguments passed to `theme()`

Examples

ggdag(m_bias()) + theme_dag_blank() # the default

ggdag(m_bias()) + theme_dag_blank() # the default

Simple grey themes for DAGs

Description

Simple grey themes for DAGs

Usage

theme_dag_grey(base_size = 12, base_family = "", ...)

theme_dag_gray(base_size = 12, base_family = "", ...)

theme_dag_grey_grid(base_size = 12, base_family = "", ...)

theme_dag_gray_grid(base_size = 12, base_family = "", ...)
theme_dag_grey(base_size = 12, base_family = "", ...)

theme_dag_gray(base_size = 12, base_family = "", ...)

theme_dag_grey_grid(base_size = 12, base_family = "", ...)

theme_dag_gray_grid(base_size = 12, base_family = "", ...)

Arguments

`base_size`	base font size, given in pts.
`base_family`	base font family
`...`	additional arguments passed to `theme()`

Examples


ggdag(m_bias()) + theme_dag_grey()

ggdag(m_bias()) + theme_dag_grey()

Tidy a `dagitty` object

Description

Tidy a dagitty object

Usage

tidy_dagitty(
  .dagitty,
  seed = NULL,
  layout = "nicely",
  ...,
  use_existing_coords = TRUE
)
tidy_dagitty(
  .dagitty,
  seed = NULL,
  layout = "nicely",
  ...,
  use_existing_coords = TRUE
)

Arguments

`.dagitty`	a `dagitty`
`seed`	a numeric seed for reproducible layout generation
`layout`	a layout available in `ggraph`. See `ggraph::create_layout()` for details. Alternatively, `"time_ordered"` will use `time_ordered_coords()` to algorithmically sort the graph by time.
`...`	optional arguments passed to `ggraph::create_layout()`
`use_existing_coords`	(Advanced). Logical. Use the coordinates produced by `dagitty::coordinates(.dagitty)`? If the coordinates are empty, `tidy_dagitty()` will generate a layout. Generally, setting this to `FALSE` is thus only useful when there is a difference in the variables coordinates and the variables in the DAG, as sometimes happens when recompiling a DAG.

Value

a tidy_dagitty object

Examples

library(dagitty)
library(ggplot2)

dag <- dagitty("dag {
  Y <- X <- Z1 <- V -> Z2 -> Y
  Z1 <- W1 <-> W2 -> Z2
  X <- W1 -> Y
  X <- W2 -> Y
  X [exposure]
  Y [outcome]
  }")

tidy_dagitty(dag)

tidy_dagitty(dag, layout = "fr") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_node() +
  geom_dag_text() +
  geom_dag_edges() +
  theme_dag()
library(dagitty)
library(ggplot2)

dag <- dagitty("dag {
  Y <- X <- Z1 <- V -> Z2 -> Y
  Z1 <- W1 <-> W2 -> Z2
  X <- W1 -> Y
  X <- W2 -> Y
  X [exposure]
  Y [outcome]
  }")

tidy_dagitty(dag)

tidy_dagitty(dag, layout = "fr") %>%
  ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
  geom_dag_node() +
  geom_dag_text() +
  geom_dag_edges() +
  theme_dag()

Create a time-ordered coordinate data frame

Description

time_ordered_coords() is a helper function to create time-ordered DAGs. Pass the results to the coords argument of dagify(). If .vars if not specified, these coordinates will be determined automatically. If you want to be specific, you can also use a list or data frame. The default is to assume you want variables to go from left to right in order by time. Variables are spread along the y-axis using a simple algorithm to stack them. You can also work along the y-axis by setting direction = "y".

Usage

time_ordered_coords(
  .vars = NULL,
  time_points = NULL,
  direction = c("x", "y"),
  auto_sort_direction = c("right", "left")
)
time_ordered_coords(
  .vars = NULL,
  time_points = NULL,
  direction = c("x", "y"),
  auto_sort_direction = c("right", "left")
)

Arguments

`.vars`	A list of character vectors, where each vector represents a single time period. Alternatively, a data frame where the first column is the variable name and the second column is the time period.
`time_points`	A vector of time points. Default is `NULL`, which creates a sequence from 1 to the number of variables.
`direction`	A character string indicating the axis along which the variables should be time-ordered. Either "x" or "y". Default is "x".
`auto_sort_direction`	If `.vars` is `NULL`: nodes will be placed as far `"left"` or `"right"` of in the graph as is reasonable. Default is right, meaning the nodes will be as close as possible in time to their descendants.

Value

A tibble with three columns: name, x, and y.

Examples


dagify(
  d ~ c1 + c2 + c3,
  c1 ~ b1 + b2,
  c3 ~ a,
  b1 ~ a,
  coords = time_ordered_coords()
) %>% ggdag()

coords <- time_ordered_coords(list(
  # time point 1
  "a",
  # time point 2
  c("b1", "b2"),
  # time point 3
  c("c1", "c2", "c3"),
  # time point 4
  "d"
))

dagify(
  d ~ c1 + c2 + c3,
  c1 ~ b1 + b2,
  c3 ~ a,
  b1 ~ a,
  coords = coords
) %>% ggdag()

# or use a data frame
x <- data.frame(
  name = c("x1", "x2", "y", "z1", "z2", "z3", "a"),
  time = c(1, 1, 2, 3, 3, 3, 4)
)
dagify(
  z3 ~ y,
  y ~ x1 + x2,
  a ~ z1 + z2 + z3,
  coords = time_ordered_coords(x)
) %>%
  ggdag()

dagify(
  d ~ c1 + c2 + c3,
  c1 ~ b1 + b2,
  c3 ~ a,
  b1 ~ a,
  coords = time_ordered_coords()
) %>% ggdag()

coords <- time_ordered_coords(list(
  # time point 1
  "a",
  # time point 2
  c("b1", "b2"),
  # time point 3
  c("c1", "c2", "c3"),
  # time point 4
  "d"
))

dagify(
  d ~ c1 + c2 + c3,
  c1 ~ b1 + b2,
  c3 ~ a,
  b1 ~ a,
  coords = coords
) %>% ggdag()

# or use a data frame
x <- data.frame(
  name = c("x1", "x2", "y", "z1", "z2", "z3", "a"),
  time = c(1, 1, 2, 3, 3, 3, 4)
)
dagify(
  z3 ~ y,
  y ~ x1 + x2,
  a ~ z1 + z2 + z3,
  coords = time_ordered_coords(x)
) %>%
  ggdag()

Find variable status

Description

Detects variable status given a DAG (exposure, outcome, latent). See dagitty::VariableStatus() for details.

Usage

node_status(.dag, as_factor = TRUE, ...)

ggdag_status(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)
node_status(.dag, as_factor = TRUE, ...)

ggdag_status(
  .tdy_dag,
  ...,
  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 = 8,
  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()
)

Arguments

`.dag`, `.tdy_dag`	input graph, an object of class `tidy_dagitty` or `dagitty`
`as_factor`	treat `status` variable as factor
`...`	additional arguments passed to `tidy_dagitty()`
`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 `⁠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 `geom_dag_label_repel()`?
`text`	The bare name of a column to use for `geom_dag_text()`. If `use_text = TRUE`, the default is to use `name`.
`label`	The bare name of a column to use for `geom_dag_label_repel()`. If `use_labels = TRUE`, the default is to use `label`.
`node`	Deprecated.
`stylized`	Deprecated.

Details

node_collider tags variable status and ggdag_collider plots all variable statuses.

Value

a tidy_dagitty with a status column for variable status or a ggplot

Examples

dag <- dagify(
  l ~ x + y,
  y ~ x,
  exposure = "x",
  outcome = "y",
  latent = "l"
)

node_status(dag)
ggdag_status(dag)

dag <- dagify(
  l ~ x + y,
  y ~ x,
  exposure = "x",
  outcome = "y",
  latent = "l"
)

node_status(dag)
ggdag_status(dag)

Package 'ggdag'

Help Index

Activate paths opened by stratifying on a collider

Description

Usage

Arguments

Value

See Also

Examples

Adjust for variables and activate any biasing paths that result

Description

Usage

Arguments

Value

Examples

Define Aesthetics for Directed Acyclic Graphs (DAGs)

Description

Usage

Arguments

Value

Examples

Convert DAGS to tidygraph

Description

Usage

Arguments

Value

Examples

Convert objects into tidy_dagitty objects

Description

Usage

Arguments

Value

See Also

Examples

Convert a tidy_dagitty object to data.frame

Description

Usage

Arguments

Convert a tidy_dagitty object to tbl

Description

Usage

Arguments

D-relationship between variables

Description

Usage

Arguments

Value

Examples

Familial relationships between variables

Description

Usage

Arguments

Value

Examples

Canonicalize a DAG

Description

Usage

Arguments

Value

Examples

Find colliders

Description

Usage

Arguments

Value

Examples

Manipulate DAG coordinates

Description

Usage

Arguments

Value

Examples

Covariate Adjustment Sets

Description

Usage

Arguments

Value

Examples

Create a dagitty DAG

Description

Convert objects into `tidy_dagitty` objects

Convert a `tidy_dagitty` object to data.frame

Convert a `tidy_dagitty` object to tbl

Dplyr verb methods for `tidy_dagitty` objects

Fortify a `tidy_dagitty` object for `ggplot2`