as_tidy_dagitty | R Documentation |
tidy_dagitty
objectsAn 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.
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",
...
)
x |
An object to convert into a |
... |
optional arguments passed to |
seed |
a numeric seed for reproducible layout generation |
layout |
a layout available in |
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
|
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 |
a tidy_dagitty
object
tidy_dagitty()
, pull_dag()
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"))
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