{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:3PVP3S3FLJCMAR6RBXVPNPWGSS","short_pith_number":"pith:3PVP3S3F","schema_version":"1.0","canonical_sha256":"dbeafdcb655a44c047d10deaf6bec694902ef1d504ae115dc538011d4d921e79","source":{"kind":"arxiv","id":"2105.14752","version":4},"attestation_state":"computed","paper":{"title":"Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"econ.EM","authors_text":"Liang Jiang, Peter C.B. Phillips, Yichong Zhang, Yubo Tao","submitted_at":"2021-05-31T07:33:31Z","abstract_excerpt":"Datasets from field experiments with covariate-adaptive randomizations (CARs) usually contain extra covariates in addition to the strata indicators. We propose to incorporate these additional covariates via auxiliary regressions in the estimation and inference of unconditional quantile treatment effects (QTEs) under CARs. We establish the consistency and limit distribution of the regression-adjusted QTE estimator and prove that the use of multiplier bootstrap inference is non-conservative under CARs. The auxiliary regression may be estimated parametrically, nonparametrically, or via regulariza"},"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":"2105.14752","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"econ.EM","submitted_at":"2021-05-31T07:33:31Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"bb7cebb5cab95d54fbfd9e096b5d73a1224f3e990dc79ee1fcbd433427cc2eb9","abstract_canon_sha256":"c34db800297b6e3a4ac5d657e680475348ffe48d1caeb3bc2048071cc550df8d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:54:14.526998Z","signature_b64":"3BqEeYRcgCgFgbuSoDpljZvq3FIS+sJhg+tc8aHKVNrprupyBhJBVy7bu8ZcTQOCBBSrz7HeZAYFiGjx6MgIBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dbeafdcb655a44c047d10deaf6bec694902ef1d504ae115dc538011d4d921e79","last_reissued_at":"2026-07-05T04:54:14.526648Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:54:14.526648Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"econ.EM","authors_text":"Liang Jiang, Peter C.B. Phillips, Yichong Zhang, Yubo Tao","submitted_at":"2021-05-31T07:33:31Z","abstract_excerpt":"Datasets from field experiments with covariate-adaptive randomizations (CARs) usually contain extra covariates in addition to the strata indicators. We propose to incorporate these additional covariates via auxiliary regressions in the estimation and inference of unconditional quantile treatment effects (QTEs) under CARs. We establish the consistency and limit distribution of the regression-adjusted QTE estimator and prove that the use of multiplier bootstrap inference is non-conservative under CARs. The auxiliary regression may be estimated parametrically, nonparametrically, or via regulariza"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.14752","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2105.14752/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2105.14752","created_at":"2026-07-05T04:54:14.526707+00:00"},{"alias_kind":"arxiv_version","alias_value":"2105.14752v4","created_at":"2026-07-05T04:54:14.526707+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.14752","created_at":"2026-07-05T04:54:14.526707+00:00"},{"alias_kind":"pith_short_12","alias_value":"3PVP3S3FLJCM","created_at":"2026-07-05T04:54:14.526707+00:00"},{"alias_kind":"pith_short_16","alias_value":"3PVP3S3FLJCMAR6R","created_at":"2026-07-05T04:54:14.526707+00:00"},{"alias_kind":"pith_short_8","alias_value":"3PVP3S3F","created_at":"2026-07-05T04:54:14.526707+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2607.04257","citing_title":"Randomization Tests in Randomized Saturation Designs","ref_index":88,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS","json":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS.json","graph_json":"https://pith.science/api/pith-number/3PVP3S3FLJCMAR6RBXVPNPWGSS/graph.json","events_json":"https://pith.science/api/pith-number/3PVP3S3FLJCMAR6RBXVPNPWGSS/events.json","paper":"https://pith.science/paper/3PVP3S3F"},"agent_actions":{"view_html":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS","download_json":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS.json","view_paper":"https://pith.science/paper/3PVP3S3F","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2105.14752&json=true","fetch_graph":"https://pith.science/api/pith-number/3PVP3S3FLJCMAR6RBXVPNPWGSS/graph.json","fetch_events":"https://pith.science/api/pith-number/3PVP3S3FLJCMAR6RBXVPNPWGSS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS/action/storage_attestation","attest_author":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS/action/author_attestation","sign_citation":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS/action/citation_signature","submit_replication":"https://pith.science/pith/3PVP3S3FLJCMAR6RBXVPNPWGSS/action/replication_record"}},"created_at":"2026-07-05T04:54:14.526707+00:00","updated_at":"2026-07-05T04:54:14.526707+00:00"}