{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:4YVULWROGZIDUB3H4O7HPWU4JT","short_pith_number":"pith:4YVULWRO","schema_version":"1.0","canonical_sha256":"e62b45da2e36503a0767e3be77da9c4cf2f37b8dea0c5edd890286b7e0c54c93","source":{"kind":"arxiv","id":"1511.08775","version":3},"attestation_state":"computed","paper":{"title":"Adjusted Priors for Bayes Factors Involving Reparameterized Order Constraints","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Daniel W. Heck, Eric-Jan Wagenmakers","submitted_at":"2015-11-27T19:51:00Z","abstract_excerpt":"Many psychological theories that are instantiated as statistical models imply order constraints on the model parameters. To fit and test such restrictions, order constraints of the form $\\theta_i \\leq \\theta_j$ can be reparameterized with auxiliary parameters $\\eta\\in [0,1]$ to replace the original parameters by $\\theta_i = \\eta\\cdot\\theta_j$. This approach is especially common in multinomial processing tree (MPT) modeling because the reparameterized, less complex model also belongs to the MPT class. Here, we discuss the importance of adjusting the prior distributions for the auxiliary paramet"},"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":"1511.08775","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-11-27T19:51:00Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"48a6532c292f675e2dc1cceb49d48aedd1b4796587c02d6513c64b64d5b5a390","abstract_canon_sha256":"de8158aa14d9326250024856e35bb10b4a9d6e60ec828be1e94116d69d5a3731"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:31.597461Z","signature_b64":"MV3qg7KKlai6R1HjjML5O05beXHdmZb0Ak+GjZc5/T+IGKnqQ23+84ycjP1KlgI6FrzA4gZC7pAtHR8yTAiXBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e62b45da2e36503a0767e3be77da9c4cf2f37b8dea0c5edd890286b7e0c54c93","last_reissued_at":"2026-05-18T00:09:31.596879Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:31.596879Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adjusted Priors for Bayes Factors Involving Reparameterized Order Constraints","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Daniel W. Heck, Eric-Jan Wagenmakers","submitted_at":"2015-11-27T19:51:00Z","abstract_excerpt":"Many psychological theories that are instantiated as statistical models imply order constraints on the model parameters. To fit and test such restrictions, order constraints of the form $\\theta_i \\leq \\theta_j$ can be reparameterized with auxiliary parameters $\\eta\\in [0,1]$ to replace the original parameters by $\\theta_i = \\eta\\cdot\\theta_j$. This approach is especially common in multinomial processing tree (MPT) modeling because the reparameterized, less complex model also belongs to the MPT class. Here, we discuss the importance of adjusting the prior distributions for the auxiliary paramet"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.08775","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":""},"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":"1511.08775","created_at":"2026-05-18T00:09:31.596968+00:00"},{"alias_kind":"arxiv_version","alias_value":"1511.08775v3","created_at":"2026-05-18T00:09:31.596968+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.08775","created_at":"2026-05-18T00:09:31.596968+00:00"},{"alias_kind":"pith_short_12","alias_value":"4YVULWROGZID","created_at":"2026-05-18T12:29:05.191682+00:00"},{"alias_kind":"pith_short_16","alias_value":"4YVULWROGZIDUB3H","created_at":"2026-05-18T12:29:05.191682+00:00"},{"alias_kind":"pith_short_8","alias_value":"4YVULWRO","created_at":"2026-05-18T12:29:05.191682+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/4YVULWROGZIDUB3H4O7HPWU4JT","json":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT.json","graph_json":"https://pith.science/api/pith-number/4YVULWROGZIDUB3H4O7HPWU4JT/graph.json","events_json":"https://pith.science/api/pith-number/4YVULWROGZIDUB3H4O7HPWU4JT/events.json","paper":"https://pith.science/paper/4YVULWRO"},"agent_actions":{"view_html":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT","download_json":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT.json","view_paper":"https://pith.science/paper/4YVULWRO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1511.08775&json=true","fetch_graph":"https://pith.science/api/pith-number/4YVULWROGZIDUB3H4O7HPWU4JT/graph.json","fetch_events":"https://pith.science/api/pith-number/4YVULWROGZIDUB3H4O7HPWU4JT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT/action/storage_attestation","attest_author":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT/action/author_attestation","sign_citation":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT/action/citation_signature","submit_replication":"https://pith.science/pith/4YVULWROGZIDUB3H4O7HPWU4JT/action/replication_record"}},"created_at":"2026-05-18T00:09:31.596968+00:00","updated_at":"2026-05-18T00:09:31.596968+00:00"}