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pith:R6WWXKTU

pith:2026:R6WWXKTULXY7IYBIV27ZX6GV64
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Transporting treatment effects by calibrating large-scale observational outcomes

Harrison H Li

By calibrating observational outcome measurements to a small experimental dataset via ordinary least squares, researchers obtain a consistent estimator for the transported average treatment effect with valid inference even without overlap.

arxiv:2605.07285 v2 · 2026-05-08 · stat.ME

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3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

our estimator is consistent for the transported average treatment effect. Otherwise, it converges to a projection estimand. As long as the observational dataset size grows sufficiently quickly relative to the experimental dataset size, our estimator achieves a notion of semiparametric efficiency proposed in recent work on semi-supervised learning for the projection estimand.

C2weakest assumption

When the calibration regression is well specified for consistency; also that the observational dataset size grows sufficiently quickly relative to the experimental dataset size for efficiency, and that OLS calibration can handle biased measurements in the observational outcome.

C3one line summary

Proposes a calibration-based estimator for transported average treatment effects that is consistent under correct specification and achieves semiparametric efficiency with large observational data.

Receipt and verification
First computed 2026-05-20T00:03:14.714087Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

8fad6baa745df1f46028aebf9bf8d5f7273c13d550475c9c4c38d98f9a55ba0d

Aliases

arxiv: 2605.07285 · arxiv_version: 2605.07285v2 · doi: 10.48550/arxiv.2605.07285 · pith_short_12: R6WWXKTULXY7 · pith_short_16: R6WWXKTULXY7IYBI · pith_short_8: R6WWXKTU
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/R6WWXKTULXY7IYBIV27ZX6GV64 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 8fad6baa745df1f46028aebf9bf8d5f7273c13d550475c9c4c38d98f9a55ba0d
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "7cd4bb0656103d745c86565386c0f8f37d6ebbb07ebbe026b173a30367f14c80",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "stat.ME",
    "submitted_at": "2026-05-08T05:48:07Z",
    "title_canon_sha256": "ea217d65772a775b0dcea9354a98c60b1384ff301f6cae884d57a34756d465ff"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.07285",
    "kind": "arxiv",
    "version": 2
  }
}