However, what we really want to include in publications is something like this:
The second one can include subscript and superscript, among many others. After some tweaking, I found a solution, not perfect but usable for now.
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library(dagitty)
library(ggdag)
library(ggraph)
library(cowplot)
library(dplyr)
```{r, echo=FALSE}
dag <- dagify(Y1 ~ X + Z1 + Z0 + U + P,
Y0 ~ Z0 + U,
X ~ Y0 + Z1 + Z0 + P,
Z1 ~ Z0,
P ~ Y0 + Z1 + Z0,
exposure = "X",
outcome = "Y1")
dag %>%
tidy_dagitty(layout = "auto", seed = 12345) %>%
arrange(name) %>%
ggplot(aes(x = x, y = y, xend = xend, yend = yend)) +
geom_dag_point() +
geom_dag_edges() +
geom_dag_text(parse = TRUE, label = c("P", "U", "X", expression(Y[0]), expression(Y[1]), expression(Z[0]), expression(Z[1]))) +
theme_dag()
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Here the trick is to sort the tidy version of the DAG data by "name", then we can assign labels by the order of the name of the nodes. I hope a more automated approach can be developed in the future.
By the way, with the package latex2exp, it is straightforward to use LaTeX instead of plotmath commands.
