{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:BZZX23TQPNJL6UVCBKTPJFIPYQ","short_pith_number":"pith:BZZX23TQ","schema_version":"1.0","canonical_sha256":"0e737d6e707b52bf52a20aa6f4950fc412ea12711cc5d333dba4ab2a070cc668","source":{"kind":"arxiv","id":"1506.08149","version":2},"attestation_state":"computed","paper":{"title":"Identification and Inference for Marginal Average Treatment Effect on the Treated With an Instrumental Variable","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Baoluo Sun, Eric Tchetgen Tchetgen, James Robins, Lan Liu, Wang Miao","submitted_at":"2015-06-26T16:37:37Z","abstract_excerpt":"In observational studies, treatments are typically not randomized and therefore estimated treatment effects may be subject to confounding bias. The instrumental variable (IV) design plays the role of a quasi-experimental handle since the IV is associated with the treatment and only affects the outcome through the treatment. In this paper, we present a novel framework for identification and inference using an IV for the marginal average treatment effect amongst the treated (ETT) in the presence of unmeasured confounding. For inference, we propose three different semiparametric approaches: (i) i"},"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":"1506.08149","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2015-06-26T16:37:37Z","cross_cats_sorted":[],"title_canon_sha256":"2da51e97919ff4f684cde11b4159929c22581fb44a082c2385b593ce25a10505","abstract_canon_sha256":"7c2df09b3e7419de386045b2e7fac65a864c5ded26bb6e5872d29ad41c81068e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:07:52.458086Z","signature_b64":"4KXB67erDLftQBe52ukffu6+xZVie9hblyEWxBDEN59Z8Xu41oc+XhApGScUmjldr1RpTyipFw6Arx27q98AAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e737d6e707b52bf52a20aa6f4950fc412ea12711cc5d333dba4ab2a070cc668","last_reissued_at":"2026-05-18T01:07:52.457624Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:07:52.457624Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Identification and Inference for Marginal Average Treatment Effect on the Treated With an Instrumental Variable","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Baoluo Sun, Eric Tchetgen Tchetgen, James Robins, Lan Liu, Wang Miao","submitted_at":"2015-06-26T16:37:37Z","abstract_excerpt":"In observational studies, treatments are typically not randomized and therefore estimated treatment effects may be subject to confounding bias. The instrumental variable (IV) design plays the role of a quasi-experimental handle since the IV is associated with the treatment and only affects the outcome through the treatment. In this paper, we present a novel framework for identification and inference using an IV for the marginal average treatment effect amongst the treated (ETT) in the presence of unmeasured confounding. For inference, we propose three different semiparametric approaches: (i) i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1506.08149","kind":"arxiv","version":2},"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":"1506.08149","created_at":"2026-05-18T01:07:52.457689+00:00"},{"alias_kind":"arxiv_version","alias_value":"1506.08149v2","created_at":"2026-05-18T01:07:52.457689+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1506.08149","created_at":"2026-05-18T01:07:52.457689+00:00"},{"alias_kind":"pith_short_12","alias_value":"BZZX23TQPNJL","created_at":"2026-05-18T12:29:14.074870+00:00"},{"alias_kind":"pith_short_16","alias_value":"BZZX23TQPNJL6UVC","created_at":"2026-05-18T12:29:14.074870+00:00"},{"alias_kind":"pith_short_8","alias_value":"BZZX23TQ","created_at":"2026-05-18T12:29:14.074870+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/BZZX23TQPNJL6UVCBKTPJFIPYQ","json":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ.json","graph_json":"https://pith.science/api/pith-number/BZZX23TQPNJL6UVCBKTPJFIPYQ/graph.json","events_json":"https://pith.science/api/pith-number/BZZX23TQPNJL6UVCBKTPJFIPYQ/events.json","paper":"https://pith.science/paper/BZZX23TQ"},"agent_actions":{"view_html":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ","download_json":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ.json","view_paper":"https://pith.science/paper/BZZX23TQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1506.08149&json=true","fetch_graph":"https://pith.science/api/pith-number/BZZX23TQPNJL6UVCBKTPJFIPYQ/graph.json","fetch_events":"https://pith.science/api/pith-number/BZZX23TQPNJL6UVCBKTPJFIPYQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ/action/storage_attestation","attest_author":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ/action/author_attestation","sign_citation":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ/action/citation_signature","submit_replication":"https://pith.science/pith/BZZX23TQPNJL6UVCBKTPJFIPYQ/action/replication_record"}},"created_at":"2026-05-18T01:07:52.457689+00:00","updated_at":"2026-05-18T01:07:52.457689+00:00"}