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  "path": "/t/the-growing-interest-in-integrating-causal-inference-and-design-theory/28581#post_14",
  "publishedAt": "2026-05-16T13:16:56.000Z",
  "site": "https://discourse.datamethods.org",
  "textContent": "stephenrho:\n\n> In a randomized experiment it is not possible for X to _cause_ treatment selection, which I would take from X → T in a conventional DAG.\n\nI realize I never answered this point. The statement that this is a RCT DAG makes treatment assignment by randomization. This step in the graph is omitted as shorthand. X here is the disease agnostic gate, a threshold of nonspecific severity values. So X besides being a selection gate is actually also a covariate for each of the different diseases it selects.\n\nThere",
  "title": "The growing interest in integrating causal inference and Design Theory"
}