library(tidyverse) # your friend and mine
library(dagitty) # for working with DAGs
library(ggdag) # for drawing DAGs in R
3.2 — DAGs — R Practice
Required Packages
Load all the required packages we will use by running (clicking the green play button) the chunk below:
set.seed(20) # using this number means all "random" generated objects will be identical for all of us!
For each of the following examples:
- Write out all of the causal pathways from
X
(treatment of interest) toY
(outcome of interest). - Identify which variable(s) need to be controlled to estimate the causal effect of
X
onY
. You can usedagitty.net
to help you, but you should start trying to recognize these on your own! - Draw the DAGs in
r
usingggdag
. After setting up the dag withdagify()
(and specifyingexposure
andoutcome
insidedagify
), pipe that intoggdag()
. Try again piping it instead intoggdag_status()
(to highlight what is X and what is Y). Try again piping it instead intoggdag_adjustment_set()
to show what needs to be controlled.
Don’t forget to install ggdag
and dagitty
!
Question 1
Part I
Pathways:
- \(X \rightarrow Y\) (causal, front door)
- \(X \leftarrow Z \rightarrow Y\) (not causal, back door)