{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreialnzwvb6hchoxwbx7tcbckko4o26iwkko2shdwkacdqgicora6rq",
    "uri": "at://did:plc:wwyqal4cnqhuwyacdj7rqq3n/app.bsky.feed.post/3meuagzwjpla2"
  },
  "path": "/t/generalizability-vs-transportability-in-trials/28551?page=3#post_41",
  "publishedAt": "2026-02-14T16:20:38.000Z",
  "site": "https://discourse.datamethods.org",
  "textContent": "I agree with your thoughts. Causal object explication clarifies “what exactly is the effect we are defining?” and external validity address a different problem, which is “what population is our causal object defined over?” As eligibility changes in a trial, these trials report different causal objects because the population component differs and that population specification is where external validity enters.\n\nIf our causal object is:\n\nE[Y(1)−Y(0)|S=1]\n\nthen asking whether it generalizes to the broader population is asking about a different causal object:\n\nE[Y(1)−Y(0)]\n\nSo external validity in analytical studies is essentially about **applicability** of one causal object to another population – and I propose we use the term applicability throughout – replacing transportability with _causal applicability_",
  "title": "Generalizability vs. Transportability in Trials"
}