## Everything

dag <- 'dag {
  bb="-4.79,-6.035,4.818,5.504"
  SES [pos="-4.463,-2.925"]
  ad_treat [pos="2.007,-1.567"]
  afli [pos="0.028,-1.851"]
  age [pos="-1.242,-0.765"]
  alc [pos="-3.716,-0.111"]
  ami [pos="-3.137,3.986"]
  civil [pos="-4.099,0.703"]
  diabetes [pos="-3.838,3.579"]
  education [pos="-3.632,-3.678"]
  gen_PA [pos="-2.820,-1.247"]
  hypertension [pos="-4.034,2.468"]
  mrs_0 [pos="-1.746,2.715"]
  mrs_1 [pos="1.326,-0.469"]
  nihss_0 [pos="0.271,1.296"]
  pase_0 [exposure,pos="-0.542,0.173"]
  revasc [pos="0.980,2.332"]
  rtreat [pos="2.334,2.036"]
  sex [pos="-4.538,-0.778"]
  smoker [pos="-1.877,-2.160"]
  stroke [adjusted,pos="0.766,0.321"]
  svd [latent,pos="-2.400,1.493"]
  tci [pos="-2.418,4.467"]
  vasc_event [outcome,pos="3.754,0.358"]
  SES -> ad_treat
  SES -> age
  SES -> alc
  SES -> gen_PA
  SES -> stroke
  SES -> vasc_event
  ad_treat -> vasc_event
  afli -> pase_0
  afli -> stroke
  afli -> vasc_event
  age -> afli
  age -> civil
  age -> mrs_1
  age -> nihss_0
  age -> vasc_event
  alc -> hypertension
  alc -> pase_0
  alc -> stroke
  alc -> svd
  alc -> vasc_event
  ami -> afli
  ami -> mrs_0
  ami -> stroke
  ami -> vasc_event
  civil -> pase_0
  civil -> stroke
  civil -> vasc_event
  diabetes -> mrs_0
  diabetes -> nihss_0
  diabetes -> stroke
  diabetes -> svd
  diabetes -> vasc_event
  education -> SES
  education -> ad_treat
  education -> age
  education -> alc
  education -> gen_PA
  education -> stroke
  education -> vasc_event
  gen_PA -> ami
  gen_PA -> diabetes
  gen_PA -> hypertension
  gen_PA -> pase_0
  gen_PA -> smoker
  gen_PA -> tci
  hypertension -> afli
  hypertension -> mrs_0
  hypertension -> nihss_0
  hypertension -> stroke
  hypertension -> svd
  hypertension -> vasc_event
  mrs_0 -> pase_0
  mrs_0 -> revasc
  mrs_1 -> ad_treat
  mrs_1 -> vasc_event
  nihss_0 -> revasc
  pase_0 -> ad_treat
  pase_0 -> nihss_0
  pase_0 -> stroke
  revasc -> mrs_1
  rtreat -> mrs_1
  rtreat -> vasc_event
  sex -> ad_treat
  sex -> alc
  sex -> education
  sex -> mrs_1
  sex -> pase_0
  sex -> stroke
  sex -> vasc_event
  smoker -> age
  smoker -> mrs_1
  smoker -> vasc_event
  stroke -> mrs_1
  stroke -> nihss_0
  stroke -> rtreat
  stroke -> vasc_event
  svd -> mrs_0
  svd -> pase_0
  svd -> vasc_event
  tci -> mrs_0
  tci -> stroke
  tci -> vasc_event
}'


## Simplified

dag <- 'dag {
bb="-4.79,-6.035,4.818,5.504"
"Higher SES" [pos="-1.671,-1.740"]
"U: higher svd score" [latent,pos="-3.091,2.172"]
"active treat" [pos="1.914,3.209"]
"higher PA" [exposure,pos="-0.999,0.555"]
"lower mrs_0" [pos="-2.437,1.259"]
ad_treat [pos="-0.448,-0.358"]
cardio_vasc [pos="-4.202,0.839"]
male [pos="-3.119,-0.926"]
vasc_event [outcome,pos="3.754,0.358"]
"Higher SES" -> "higher PA"
"Higher SES" -> ad_treat
"Higher SES" -> vasc_event
"U: higher svd score" -> "lower mrs_0"
"U: higher svd score" -> vasc_event
"active treat" -> vasc_event
"higher PA" -> ad_treat
"higher PA" -> vasc_event
"lower mrs_0" -> "higher PA"
ad_treat -> vasc_event
cardio_vasc -> "U: higher svd score"
cardio_vasc -> "higher PA" [pos="-2.876,-0.185"]
cardio_vasc -> "lower mrs_0"
cardio_vasc -> vasc_event [pos="-4.762,5.060"]
male -> "higher PA"
male -> vasc_event [pos="-2.540,-5.134"]
}'

dag |> ggdag::ggdag_adjustment_set(node_size = 14, text_col = "black") + 
  theme(legend.position = "bottom")