{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:VL7LEPNFGTNCIVXQ4PIUFKSEGP","short_pith_number":"pith:VL7LEPNF","canonical_record":{"source":{"id":"2210.07324","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-10-13T19:47:12Z","cross_cats_sorted":[],"title_canon_sha256":"ee8b5152dc4ba0bb4389e129fdeae48922a0f4a74da08bd7b149ae90e9e0ab3c","abstract_canon_sha256":"9a920c8956775cffbd9778c2cb82a434d003b79b526363f66d978b6929e88d7a"},"schema_version":"1.0"},"canonical_sha256":"aafeb23da534da2456f0e3d142aa4433def00a92b6f10319889b833d7cb7f2cb","source":{"kind":"arxiv","id":"2210.07324","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.07324","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"arxiv_version","alias_value":"2210.07324v3","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.07324","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"pith_short_12","alias_value":"VL7LEPNFGTNC","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"pith_short_16","alias_value":"VL7LEPNFGTNCIVXQ","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"pith_short_8","alias_value":"VL7LEPNF","created_at":"2026-07-05T07:21:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:VL7LEPNFGTNCIVXQ4PIUFKSEGP","target":"record","payload":{"canonical_record":{"source":{"id":"2210.07324","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-10-13T19:47:12Z","cross_cats_sorted":[],"title_canon_sha256":"ee8b5152dc4ba0bb4389e129fdeae48922a0f4a74da08bd7b149ae90e9e0ab3c","abstract_canon_sha256":"9a920c8956775cffbd9778c2cb82a434d003b79b526363f66d978b6929e88d7a"},"schema_version":"1.0"},"canonical_sha256":"aafeb23da534da2456f0e3d142aa4433def00a92b6f10319889b833d7cb7f2cb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:21:09.988968Z","signature_b64":"8iCbPTcEkcd+U3XuV4aSJqRlKhuqgT2DrRb+Wxj2seSsMf6NvlFiqWo1WApQt8FCWj1jsZAc92rjUxH7g+CEBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aafeb23da534da2456f0e3d142aa4433def00a92b6f10319889b833d7cb7f2cb","last_reissued_at":"2026-07-05T07:21:09.988454Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:21:09.988454Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.07324","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:21:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B2c5noqOUaEAjZfV1gEg6DDOvL2sK9Ckft4jVW0KEJAPvnz8BBB0viqu1Hny8Zv1EJKG43rwZYsPPOUom6vEDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T07:10:47.884048Z"},"content_sha256":"b80274319baf06f6c4bc7a43eae1c11ddd79c986006ab096ca7dd385ef33443e","schema_version":"1.0","event_id":"sha256:b80274319baf06f6c4bc7a43eae1c11ddd79c986006ab096ca7dd385ef33443e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:VL7LEPNFGTNCIVXQ4PIUFKSEGP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Model-robust and efficient covariate adjustment for cluster-randomized experiments","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Bingkai Wang, Chan Park, Dylan S. Small, Fan Li","submitted_at":"2022-10-13T19:47:12Z","abstract_excerpt":"Cluster-randomized experiments are increasingly used to evaluate interventions in routine practice conditions, and researchers often adopt model-based methods with covariate adjustment in the statistical analyses. However, the validity of model-based covariate adjustment is unclear when the working models are misspecified, leading to ambiguity of estimands and risk of bias. In this article, we first adapt two conventional model-based methods, generalized estimating equations and linear mixed models, with weighted g-computation to achieve robust inference for cluster-average and individual-aver"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.07324","kind":"arxiv","version":3},"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/2210.07324/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:21:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o/M1EPEypAHEAgJsmTapnRYrFqMqn3Hu7VutaxOJdj6fyLAUg2dp0hTZ86aUAJR958KZKKkbCaPdONB0eoQtBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T07:10:47.884559Z"},"content_sha256":"86af02ddc061cf0bc74e9e314ed96fd8ee9420c09fc5159abce08ef49267ea9c","schema_version":"1.0","event_id":"sha256:86af02ddc061cf0bc74e9e314ed96fd8ee9420c09fc5159abce08ef49267ea9c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VL7LEPNFGTNCIVXQ4PIUFKSEGP/bundle.json","state_url":"https://pith.science/pith/VL7LEPNFGTNCIVXQ4PIUFKSEGP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VL7LEPNFGTNCIVXQ4PIUFKSEGP/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-06T07:10:47Z","links":{"resolver":"https://pith.science/pith/VL7LEPNFGTNCIVXQ4PIUFKSEGP","bundle":"https://pith.science/pith/VL7LEPNFGTNCIVXQ4PIUFKSEGP/bundle.json","state":"https://pith.science/pith/VL7LEPNFGTNCIVXQ4PIUFKSEGP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VL7LEPNFGTNCIVXQ4PIUFKSEGP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:VL7LEPNFGTNCIVXQ4PIUFKSEGP","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":"9a920c8956775cffbd9778c2cb82a434d003b79b526363f66d978b6929e88d7a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-10-13T19:47:12Z","title_canon_sha256":"ee8b5152dc4ba0bb4389e129fdeae48922a0f4a74da08bd7b149ae90e9e0ab3c"},"schema_version":"1.0","source":{"id":"2210.07324","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.07324","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"arxiv_version","alias_value":"2210.07324v3","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.07324","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"pith_short_12","alias_value":"VL7LEPNFGTNC","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"pith_short_16","alias_value":"VL7LEPNFGTNCIVXQ","created_at":"2026-07-05T07:21:09Z"},{"alias_kind":"pith_short_8","alias_value":"VL7LEPNF","created_at":"2026-07-05T07:21:09Z"}],"graph_snapshots":[{"event_id":"sha256:86af02ddc061cf0bc74e9e314ed96fd8ee9420c09fc5159abce08ef49267ea9c","target":"graph","created_at":"2026-07-05T07:21:09Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2210.07324/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cluster-randomized experiments are increasingly used to evaluate interventions in routine practice conditions, and researchers often adopt model-based methods with covariate adjustment in the statistical analyses. However, the validity of model-based covariate adjustment is unclear when the working models are misspecified, leading to ambiguity of estimands and risk of bias. In this article, we first adapt two conventional model-based methods, generalized estimating equations and linear mixed models, with weighted g-computation to achieve robust inference for cluster-average and individual-aver","authors_text":"Bingkai Wang, Chan Park, Dylan S. Small, Fan Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-10-13T19:47:12Z","title":"Model-robust and efficient covariate adjustment for cluster-randomized experiments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.07324","kind":"arxiv","version":3},"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:b80274319baf06f6c4bc7a43eae1c11ddd79c986006ab096ca7dd385ef33443e","target":"record","created_at":"2026-07-05T07:21:09Z","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":"9a920c8956775cffbd9778c2cb82a434d003b79b526363f66d978b6929e88d7a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-10-13T19:47:12Z","title_canon_sha256":"ee8b5152dc4ba0bb4389e129fdeae48922a0f4a74da08bd7b149ae90e9e0ab3c"},"schema_version":"1.0","source":{"id":"2210.07324","kind":"arxiv","version":3}},"canonical_sha256":"aafeb23da534da2456f0e3d142aa4433def00a92b6f10319889b833d7cb7f2cb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aafeb23da534da2456f0e3d142aa4433def00a92b6f10319889b833d7cb7f2cb","first_computed_at":"2026-07-05T07:21:09.988454Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:21:09.988454Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8iCbPTcEkcd+U3XuV4aSJqRlKhuqgT2DrRb+Wxj2seSsMf6NvlFiqWo1WApQt8FCWj1jsZAc92rjUxH7g+CEBA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:21:09.988968Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.07324","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b80274319baf06f6c4bc7a43eae1c11ddd79c986006ab096ca7dd385ef33443e","sha256:86af02ddc061cf0bc74e9e314ed96fd8ee9420c09fc5159abce08ef49267ea9c"],"state_sha256":"7c52203c27b099d2eaef2e0c1a1502143a5702f84f2457e4cf90ca284104186f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wdfcKE9SoxNMqycnWmkG7KQBD4EvX7e8nHMiUI2sfYDiCv3OFIb2rvrFWk9CDbgx1GfmWA9EfcZWNz4AjJ6vCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T07:10:47.889180Z","bundle_sha256":"4d40ed9d5e07eed2cae1ad9e62a3021c694630abb9d7aa03b4007459eb67bb41"}}