{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:36JWCEVGCUBSII3MJBRQ6RLVDD","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8db2f5f57a2140b864852eeb61bd85e899ab2697e6438d4fad8af8a23c2eb881","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-11-06T13:01:48Z","title_canon_sha256":"bf4cffe26dfcf01db031fb185c266ffe35bfbc0e085b30d117eb8d04f6613fc6"},"schema_version":"1.0","source":{"id":"1211.1208","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1211.1208","created_at":"2026-05-18T03:41:22Z"},{"alias_kind":"arxiv_version","alias_value":"1211.1208v1","created_at":"2026-05-18T03:41:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1211.1208","created_at":"2026-05-18T03:41:22Z"},{"alias_kind":"pith_short_12","alias_value":"36JWCEVGCUBS","created_at":"2026-05-18T12:26:50Z"},{"alias_kind":"pith_short_16","alias_value":"36JWCEVGCUBSII3M","created_at":"2026-05-18T12:26:50Z"},{"alias_kind":"pith_short_8","alias_value":"36JWCEVG","created_at":"2026-05-18T12:26:50Z"}],"graph_snapshots":[{"event_id":"sha256:7f5e9ef540d2d2a32a2eaa68741bb2012a4664ecd3e43f2ed10e5459e6d8f8db","target":"graph","created_at":"2026-05-18T03:41:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"While linear mixed modeling methods are foundational concepts introduced in any statistical education, adequate general methods for interval estimation involving models with more than a few variance components are lacking, especially in the unbalanced setting. Generalized fiducial inference provides a possible framework that accommodates this absence of methodology. Under the fabric of generalized fiducial inference along with sequential Monte Carlo methods, we present an approach for interval estimation for both balanced and unbalanced Gaussian linear mixed models. We compare the proposed met","authors_text":"Jan Hannig, Jessi Cisewski","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-11-06T13:01:48Z","title":"Generalized fiducial inference for normal linear mixed models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1211.1208","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:151a85f6abf697e976620356f3e04e3ccb1f4db2041fc7267cdac60b31f29bd6","target":"record","created_at":"2026-05-18T03:41:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"8db2f5f57a2140b864852eeb61bd85e899ab2697e6438d4fad8af8a23c2eb881","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-11-06T13:01:48Z","title_canon_sha256":"bf4cffe26dfcf01db031fb185c266ffe35bfbc0e085b30d117eb8d04f6613fc6"},"schema_version":"1.0","source":{"id":"1211.1208","kind":"arxiv","version":1}},"canonical_sha256":"df936112a6150324236c48630f457518d46a3649bc1beecb881448828fba3fce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df936112a6150324236c48630f457518d46a3649bc1beecb881448828fba3fce","first_computed_at":"2026-05-18T03:41:22.054367Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:41:22.054367Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1ZDA3VrriVzMH1xp981rcW+OlzmjqZbHNGDQ1wcPWQCVA2dlrxtqtZkqGP8+FjfAyC4wYhUtbOjix1mtMeETDA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:41:22.054794Z","signed_message":"canonical_sha256_bytes"},"source_id":"1211.1208","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:151a85f6abf697e976620356f3e04e3ccb1f4db2041fc7267cdac60b31f29bd6","sha256:7f5e9ef540d2d2a32a2eaa68741bb2012a4664ecd3e43f2ed10e5459e6d8f8db"],"state_sha256":"8d35a84ad99d483d00074cd59ed2e01c3c29cf028d9415938d1b99f47a198535"}