{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:G2OQEYCK64ELFKI2ZS4XSMCP33","short_pith_number":"pith:G2OQEYCK","schema_version":"1.0","canonical_sha256":"369d02604af708b2a91accb979304fdec784cd28f1d1ac9ed8935afc695e7e44","source":{"kind":"arxiv","id":"1104.2400","version":1},"attestation_state":"computed","paper":{"title":"Block-Conditional Missing at Random Models for Missing Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"John D. Kalbfleisch, Roderick J. A. Little, Yan Zhou","submitted_at":"2011-04-13T07:39:13Z","abstract_excerpt":"Two major ideas in the analysis of missing data are (a) the EM algorithm [Dempster, Laird and Rubin, J. Roy. Statist. Soc. Ser. B 39 (1977) 1--38] for maximum likelihood (ML) estimation, and (b) the formulation of models for the joint distribution of the data ${Z}$ and missing data indicators ${M}$, and associated \"missing at random\"; (MAR) condition under which a model for ${M}$ is unnecessary [Rubin, Biometrika 63 (1976) 581--592]. Most previous work has treated ${Z}$ and ${M}$ as single blocks, yielding selection or pattern-mixture models depending on how their joint distribution is factori"},"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":"1104.2400","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-04-13T07:39:13Z","cross_cats_sorted":[],"title_canon_sha256":"ae3341ba464ae410f8a499c39d71bb47c07dfb2333c440f920d607f6d09830b8","abstract_canon_sha256":"a296bb1b5f90258a206e4e95e6e8f20a8405fac3aeccd65132f640d67defff89"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:24:34.826783Z","signature_b64":"exxabsGBmTMUlAiPkC21g+JokE17QrgG8zw64XkW8qzRQTrEA05gPxh2HePUaVLFgBy8VmIVkTsSfTCJuKcyAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"369d02604af708b2a91accb979304fdec784cd28f1d1ac9ed8935afc695e7e44","last_reissued_at":"2026-05-18T04:24:34.826415Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:24:34.826415Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Block-Conditional Missing at Random Models for Missing Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"John D. Kalbfleisch, Roderick J. A. Little, Yan Zhou","submitted_at":"2011-04-13T07:39:13Z","abstract_excerpt":"Two major ideas in the analysis of missing data are (a) the EM algorithm [Dempster, Laird and Rubin, J. Roy. Statist. Soc. Ser. B 39 (1977) 1--38] for maximum likelihood (ML) estimation, and (b) the formulation of models for the joint distribution of the data ${Z}$ and missing data indicators ${M}$, and associated \"missing at random\"; (MAR) condition under which a model for ${M}$ is unnecessary [Rubin, Biometrika 63 (1976) 581--592]. Most previous work has treated ${Z}$ and ${M}$ as single blocks, yielding selection or pattern-mixture models depending on how their joint distribution is factori"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1104.2400","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":"1104.2400","created_at":"2026-05-18T04:24:34.826470+00:00"},{"alias_kind":"arxiv_version","alias_value":"1104.2400v1","created_at":"2026-05-18T04:24:34.826470+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1104.2400","created_at":"2026-05-18T04:24:34.826470+00:00"},{"alias_kind":"pith_short_12","alias_value":"G2OQEYCK64EL","created_at":"2026-05-18T12:26:28.662955+00:00"},{"alias_kind":"pith_short_16","alias_value":"G2OQEYCK64ELFKI2","created_at":"2026-05-18T12:26:28.662955+00:00"},{"alias_kind":"pith_short_8","alias_value":"G2OQEYCK","created_at":"2026-05-18T12:26:28.662955+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/G2OQEYCK64ELFKI2ZS4XSMCP33","json":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33.json","graph_json":"https://pith.science/api/pith-number/G2OQEYCK64ELFKI2ZS4XSMCP33/graph.json","events_json":"https://pith.science/api/pith-number/G2OQEYCK64ELFKI2ZS4XSMCP33/events.json","paper":"https://pith.science/paper/G2OQEYCK"},"agent_actions":{"view_html":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33","download_json":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33.json","view_paper":"https://pith.science/paper/G2OQEYCK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1104.2400&json=true","fetch_graph":"https://pith.science/api/pith-number/G2OQEYCK64ELFKI2ZS4XSMCP33/graph.json","fetch_events":"https://pith.science/api/pith-number/G2OQEYCK64ELFKI2ZS4XSMCP33/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33/action/timestamp_anchor","attest_storage":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33/action/storage_attestation","attest_author":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33/action/author_attestation","sign_citation":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33/action/citation_signature","submit_replication":"https://pith.science/pith/G2OQEYCK64ELFKI2ZS4XSMCP33/action/replication_record"}},"created_at":"2026-05-18T04:24:34.826470+00:00","updated_at":"2026-05-18T04:24:34.826470+00:00"}