pith:6LZI6IQX
Creating treatment and component hierarchies in component network meta-analysis
A workflow identifies uniquely estimable relative effects to build valid treatment hierarchies in component network meta-analysis.
arxiv:2605.15142 v1 · 2026-05-14 · stat.ME
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Claims
We present a step-by-step workflow for answering treatment hierarchy questions in both frequentist and Bayesian CNMA, including explicitly identifying the uniquely estimable relative effects.
That identifying uniquely estimable relative effects is always feasible from the network structure and sufficient to construct valid non-misleading hierarchies without further assumptions on connectivity or data.
A workflow for treatment hierarchies in CNMA that identifies uniquely estimable relative effects in frequentist and Bayesian settings.
References
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| First computed | 2026-05-17T21:40:25.556870Z |
|---|---|
| Last reissued | 2026-05-17T21:57:18.877080Z |
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | unsigned_v0 |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/6LZI6IQXZBUJNRWYIMKUM727K2 \
| 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: f2f28f2217c86896c6d84315467f5f5688684ba979822a29ea2f6e47af307ebc
Canonical record JSON
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