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.

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

## Arguments

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

## Value

a dagitty DAG

dag(), coords2df(), coords2list()

## Examples


dagify(y ~ x + z, x~ z)#> dag {
#> x
#> y
#> z
#> x -> y
#> z -> x
#> z -> y
#> }
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)#> [1] TRUE
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)