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

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)
#> 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)