{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:VTK6QUYNPHTOGNU6VNMDI3J62A","short_pith_number":"pith:VTK6QUYN","canonical_record":{"source":{"id":"1306.0964","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-06-05T02:49:13Z","cross_cats_sorted":[],"title_canon_sha256":"1e10726aacfc7bd6b6bce048b922f2350f55fc05722be490d2a203679cb23a3b","abstract_canon_sha256":"aad6ab2a3fd40b8ad29778819a05be6a0166f8c6b071e665d3b12165ed1afc64"},"schema_version":"1.0"},"canonical_sha256":"acd5e8530d79e6e3369eab58346d3ed02a4d0a23c9a07324c7e72a18f921a760","source":{"kind":"arxiv","id":"1306.0964","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1306.0964","created_at":"2026-05-18T00:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1306.0964v1","created_at":"2026-05-18T00:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1306.0964","created_at":"2026-05-18T00:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"VTK6QUYNPHTO","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_16","alias_value":"VTK6QUYNPHTOGNU6","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_8","alias_value":"VTK6QUYN","created_at":"2026-05-18T12:28:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:VTK6QUYNPHTOGNU6VNMDI3J62A","target":"record","payload":{"canonical_record":{"source":{"id":"1306.0964","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-06-05T02:49:13Z","cross_cats_sorted":[],"title_canon_sha256":"1e10726aacfc7bd6b6bce048b922f2350f55fc05722be490d2a203679cb23a3b","abstract_canon_sha256":"aad6ab2a3fd40b8ad29778819a05be6a0166f8c6b071e665d3b12165ed1afc64"},"schema_version":"1.0"},"canonical_sha256":"acd5e8530d79e6e3369eab58346d3ed02a4d0a23c9a07324c7e72a18f921a760","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:56:51.884771Z","signature_b64":"BSO8DTZQIwPl+hiBIFXBaa9xUPLDLyYP97Gdo8ZaYdTJkgZaE7+0En4WOoQDnhDudZxBN+fiMID2vemlW1paCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"acd5e8530d79e6e3369eab58346d3ed02a4d0a23c9a07324c7e72a18f921a760","last_reissued_at":"2026-05-18T00:56:51.884312Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:56:51.884312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1306.0964","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XrtYzojVFjAJqnXb+4cYuqPl5+CEvmlppohY5OODLMJPV4h8LCuiNLvEBehjNK/IsJldkyF3Zn5mfKM5WxQECw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T08:27:18.256885Z"},"content_sha256":"3d7dc501bc2c69049e55e5b355906c316f49d90c87c8d5ecbc1ec2bb6d06f8a7","schema_version":"1.0","event_id":"sha256:3d7dc501bc2c69049e55e5b355906c316f49d90c87c8d5ecbc1ec2bb6d06f8a7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:VTK6QUYNPHTOGNU6VNMDI3J62A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimal Tests of Treatment Effects for the Overall Population and Two Subpopulations in Randomized Trials, using Sparse Linear Programming","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"and En-Hsu Yen, Han Liu, Michael Rosenblum","submitted_at":"2013-06-05T02:49:13Z","abstract_excerpt":"We propose new, optimal methods for analyzing randomized trials, when it is suspected that treatment effects may differ in two predefined subpopulations. Such sub-populations could be defined by a biomarker or risk factor measured at baseline. The goal is to simultaneously learn which subpopulations benefit from an experimental treatment, while providing strong control of the familywise Type I error rate. We formalize this as a multiple testing problem and show it is computationally infeasible to solve using existing techniques. Our solution involves a novel approach, in which we first transfo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1306.0964","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RLRJwTWV0gZ4Q2h9h81njqeS3Xc4qgJExtjXa0OI9iD845TkPCztr3u/lHRYkEp7jxwNIHka29HSwm8s8mg4AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T08:27:18.257813Z"},"content_sha256":"d01fb417fdb6a3c23ac4b1a8cdf3cc5425a55b2c4727629b7f36b3c897250217","schema_version":"1.0","event_id":"sha256:d01fb417fdb6a3c23ac4b1a8cdf3cc5425a55b2c4727629b7f36b3c897250217"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VTK6QUYNPHTOGNU6VNMDI3J62A/bundle.json","state_url":"https://pith.science/pith/VTK6QUYNPHTOGNU6VNMDI3J62A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VTK6QUYNPHTOGNU6VNMDI3J62A/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":"2026-06-11T08:27:18Z","links":{"resolver":"https://pith.science/pith/VTK6QUYNPHTOGNU6VNMDI3J62A","bundle":"https://pith.science/pith/VTK6QUYNPHTOGNU6VNMDI3J62A/bundle.json","state":"https://pith.science/pith/VTK6QUYNPHTOGNU6VNMDI3J62A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VTK6QUYNPHTOGNU6VNMDI3J62A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:VTK6QUYNPHTOGNU6VNMDI3J62A","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":"aad6ab2a3fd40b8ad29778819a05be6a0166f8c6b071e665d3b12165ed1afc64","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-06-05T02:49:13Z","title_canon_sha256":"1e10726aacfc7bd6b6bce048b922f2350f55fc05722be490d2a203679cb23a3b"},"schema_version":"1.0","source":{"id":"1306.0964","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1306.0964","created_at":"2026-05-18T00:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1306.0964v1","created_at":"2026-05-18T00:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1306.0964","created_at":"2026-05-18T00:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"VTK6QUYNPHTO","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_16","alias_value":"VTK6QUYNPHTOGNU6","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_8","alias_value":"VTK6QUYN","created_at":"2026-05-18T12:28:04Z"}],"graph_snapshots":[{"event_id":"sha256:d01fb417fdb6a3c23ac4b1a8cdf3cc5425a55b2c4727629b7f36b3c897250217","target":"graph","created_at":"2026-05-18T00:56:51Z","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":"We propose new, optimal methods for analyzing randomized trials, when it is suspected that treatment effects may differ in two predefined subpopulations. Such sub-populations could be defined by a biomarker or risk factor measured at baseline. The goal is to simultaneously learn which subpopulations benefit from an experimental treatment, while providing strong control of the familywise Type I error rate. We formalize this as a multiple testing problem and show it is computationally infeasible to solve using existing techniques. Our solution involves a novel approach, in which we first transfo","authors_text":"and En-Hsu Yen, Han Liu, Michael Rosenblum","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-06-05T02:49:13Z","title":"Optimal Tests of Treatment Effects for the Overall Population and Two Subpopulations in Randomized Trials, using Sparse Linear Programming"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1306.0964","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":"sha256:3d7dc501bc2c69049e55e5b355906c316f49d90c87c8d5ecbc1ec2bb6d06f8a7","target":"record","created_at":"2026-05-18T00:56:51Z","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":"aad6ab2a3fd40b8ad29778819a05be6a0166f8c6b071e665d3b12165ed1afc64","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-06-05T02:49:13Z","title_canon_sha256":"1e10726aacfc7bd6b6bce048b922f2350f55fc05722be490d2a203679cb23a3b"},"schema_version":"1.0","source":{"id":"1306.0964","kind":"arxiv","version":1}},"canonical_sha256":"acd5e8530d79e6e3369eab58346d3ed02a4d0a23c9a07324c7e72a18f921a760","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"acd5e8530d79e6e3369eab58346d3ed02a4d0a23c9a07324c7e72a18f921a760","first_computed_at":"2026-05-18T00:56:51.884312Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:56:51.884312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BSO8DTZQIwPl+hiBIFXBaa9xUPLDLyYP97Gdo8ZaYdTJkgZaE7+0En4WOoQDnhDudZxBN+fiMID2vemlW1paCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:56:51.884771Z","signed_message":"canonical_sha256_bytes"},"source_id":"1306.0964","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d7dc501bc2c69049e55e5b355906c316f49d90c87c8d5ecbc1ec2bb6d06f8a7","sha256:d01fb417fdb6a3c23ac4b1a8cdf3cc5425a55b2c4727629b7f36b3c897250217"],"state_sha256":"41e37d465117cd3f7c57c79337329b00a7d65ec9aaf74e6d9f24d40899ffd785"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rpMs46dXZceTyLuFapuvx7VTRdqp5qDM+iFu3DpIKwWGHpT+uKv23KvYcMucB8XJIqnLtjj19r0RSFJhpniwBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T08:27:18.266995Z","bundle_sha256":"8fd34fbdb40827da24f68c071ad449c05bac6928c85997a4cd0581fb429b486f"}}