{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:ZM3VSHJMIVROIGU6GDRDPELSCL","short_pith_number":"pith:ZM3VSHJM","schema_version":"1.0","canonical_sha256":"cb37591d2c4562e41a9e30e237917212e2890cf44e2ceef65f15c073fc658bc7","source":{"kind":"arxiv","id":"1806.01042","version":1},"attestation_state":"computed","paper":{"title":"pammtools: Piece-wise exponential Additive Mixed Modeling tools","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Andreas Bender, Fabian Scheipl","submitted_at":"2018-06-04T10:55:43Z","abstract_excerpt":"This article introduces the pammtools package, which facilitates data transformation, estimation and interpretation of Piece-wise exponential Additive Mixed Models. A special focus is on time-varying effects and cumulative effects of time-dependent covariates, where multiple past observations of a covariate can cumulatively affect the hazard, possibly weighted by a non-linear function. The package provides functions for convenient simulation and visualization of such effects as well as a robust and versatile function to transform time-to-event data from standard formats to a format suitable fo"},"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":"1806.01042","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2018-06-04T10:55:43Z","cross_cats_sorted":[],"title_canon_sha256":"3cd5e99363018b405f9ab97da2eab17f6ffdb54150ca4c529c061cfc0ad65160","abstract_canon_sha256":"c39d59344ed056875505857454cd2c0dcb8afb23e42160d30a5b656f23d93e41"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:17.651880Z","signature_b64":"+twDPCA4Gi2yPK/h1ehd5trMsfAbxFgd8AXFV5UI+ktr5lkmvEBbAdLf1+iuvJJcZyiO3IanNbjoSqeasUm7BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb37591d2c4562e41a9e30e237917212e2890cf44e2ceef65f15c073fc658bc7","last_reissued_at":"2026-05-18T00:14:17.651364Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:17.651364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"pammtools: Piece-wise exponential Additive Mixed Modeling tools","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Andreas Bender, Fabian Scheipl","submitted_at":"2018-06-04T10:55:43Z","abstract_excerpt":"This article introduces the pammtools package, which facilitates data transformation, estimation and interpretation of Piece-wise exponential Additive Mixed Models. A special focus is on time-varying effects and cumulative effects of time-dependent covariates, where multiple past observations of a covariate can cumulatively affect the hazard, possibly weighted by a non-linear function. The package provides functions for convenient simulation and visualization of such effects as well as a robust and versatile function to transform time-to-event data from standard formats to a format suitable fo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.01042","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":"1806.01042","created_at":"2026-05-18T00:14:17.651457+00:00"},{"alias_kind":"arxiv_version","alias_value":"1806.01042v1","created_at":"2026-05-18T00:14:17.651457+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.01042","created_at":"2026-05-18T00:14:17.651457+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZM3VSHJMIVRO","created_at":"2026-05-18T12:33:07.085635+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZM3VSHJMIVROIGU6","created_at":"2026-05-18T12:33:07.085635+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZM3VSHJM","created_at":"2026-05-18T12:33:07.085635+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2406.04098","citing_title":"A Large-Scale Neutral Comparison Study of Survival Models on Low-Dimensional Data","ref_index":10,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL","json":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL.json","graph_json":"https://pith.science/api/pith-number/ZM3VSHJMIVROIGU6GDRDPELSCL/graph.json","events_json":"https://pith.science/api/pith-number/ZM3VSHJMIVROIGU6GDRDPELSCL/events.json","paper":"https://pith.science/paper/ZM3VSHJM"},"agent_actions":{"view_html":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL","download_json":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL.json","view_paper":"https://pith.science/paper/ZM3VSHJM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1806.01042&json=true","fetch_graph":"https://pith.science/api/pith-number/ZM3VSHJMIVROIGU6GDRDPELSCL/graph.json","fetch_events":"https://pith.science/api/pith-number/ZM3VSHJMIVROIGU6GDRDPELSCL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL/action/storage_attestation","attest_author":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL/action/author_attestation","sign_citation":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL/action/citation_signature","submit_replication":"https://pith.science/pith/ZM3VSHJMIVROIGU6GDRDPELSCL/action/replication_record"}},"created_at":"2026-05-18T00:14:17.651457+00:00","updated_at":"2026-05-18T00:14:17.651457+00:00"}