{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:W5Y4KED3PRK5O7Q4P4SLZQHIX2","short_pith_number":"pith:W5Y4KED3","schema_version":"1.0","canonical_sha256":"b771c5107b7c55d77e1c7f24bcc0e8be94d28f015b756c5b2a29a9c2ab9f0be4","source":{"kind":"arxiv","id":"1902.10613","version":1},"attestation_state":"computed","paper":{"title":"Bayesian data fusion for unmeasured confounding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Brent A. Coull, Corwin Zigler, Leah Comment, Linda Valeri","submitted_at":"2019-02-27T16:12:00Z","abstract_excerpt":"Bayesian causal inference offers a principled approach to policy evaluation of proposed interventions on mediators or time-varying exposures. We outline a general approach to the estimation of causal quantities for settings with time-varying confounding, such as exposure-induced mediator-outcome confounders. We further extend this approach to propose two Bayesian data fusion (BDF) methods for unmeasured confounding. Using informative priors on quantities relating to the confounding bias parameters, our methods incorporate data from an external source where the confounder is measured in order t"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1902.10613","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-02-27T16:12:00Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"cbe6683c9aad688d0b901e88cfb737211763ba7ba9d17b5bb7a1407360b3144c","abstract_canon_sha256":"61faccc04019a15e3f4fb167d2a4e99a516eec1fb52a892c849bb1cb6a3c3912"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:30.393510Z","signature_b64":"ctsubGh6kB/Qy4xgpF1/LhUVkJaPr2x7KFMPxdLvpaNzCfh52IRRYlOrb563ddpcSlIDqtNUUzYdji1lR1RHCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b771c5107b7c55d77e1c7f24bcc0e8be94d28f015b756c5b2a29a9c2ab9f0be4","last_reissued_at":"2026-05-17T23:52:30.392931Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:30.392931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bayesian data fusion for unmeasured confounding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Brent A. Coull, Corwin Zigler, Leah Comment, Linda Valeri","submitted_at":"2019-02-27T16:12:00Z","abstract_excerpt":"Bayesian causal inference offers a principled approach to policy evaluation of proposed interventions on mediators or time-varying exposures. We outline a general approach to the estimation of causal quantities for settings with time-varying confounding, such as exposure-induced mediator-outcome confounders. We further extend this approach to propose two Bayesian data fusion (BDF) methods for unmeasured confounding. Using informative priors on quantities relating to the confounding bias parameters, our methods incorporate data from an external source where the confounder is measured in order t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.10613","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1902.10613","created_at":"2026-05-17T23:52:30.393011+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.10613v1","created_at":"2026-05-17T23:52:30.393011+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.10613","created_at":"2026-05-17T23:52:30.393011+00:00"},{"alias_kind":"pith_short_12","alias_value":"W5Y4KED3PRK5","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_16","alias_value":"W5Y4KED3PRK5O7Q4","created_at":"2026-05-18T12:33:30.264802+00:00"},{"alias_kind":"pith_short_8","alias_value":"W5Y4KED3","created_at":"2026-05-18T12:33:30.264802+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2","json":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2.json","graph_json":"https://pith.science/api/pith-number/W5Y4KED3PRK5O7Q4P4SLZQHIX2/graph.json","events_json":"https://pith.science/api/pith-number/W5Y4KED3PRK5O7Q4P4SLZQHIX2/events.json","paper":"https://pith.science/paper/W5Y4KED3"},"agent_actions":{"view_html":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2","download_json":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2.json","view_paper":"https://pith.science/paper/W5Y4KED3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.10613&json=true","fetch_graph":"https://pith.science/api/pith-number/W5Y4KED3PRK5O7Q4P4SLZQHIX2/graph.json","fetch_events":"https://pith.science/api/pith-number/W5Y4KED3PRK5O7Q4P4SLZQHIX2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2/action/storage_attestation","attest_author":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2/action/author_attestation","sign_citation":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2/action/citation_signature","submit_replication":"https://pith.science/pith/W5Y4KED3PRK5O7Q4P4SLZQHIX2/action/replication_record"}},"created_at":"2026-05-17T23:52:30.393011+00:00","updated_at":"2026-05-17T23:52:30.393011+00:00"}