{"id":"W4391823628","doi":"10.32920/25219319.v1","title":"Equivalence Testing for Multiple Regression","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Mental Health Research Topics","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"","keywords":"Equivalence (formal languages); Null hypothesis; Regression; Econometrics; Regression testing; Null (SQL); Regression analysis; Outcome (game theory); Mathematics; Statistics; Statistical hypothesis testing; Psychology; Computer science; Mathematical economics; Data mining; Discrete mathematics; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1374473,0.002604799,0.003797391,0.006223268,0.002030706,0.004979923,0.004106213,0.003124789,0.01521465],"category_scores_gemma":[0.5641922,0.001278233,0.004953816,0.007111123,0.009863705,0.0077731,0.00727554,0.009372234,0.004586804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002685441,"about_ca_system_score_gemma":0.005497611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002598908,"about_ca_topic_score_gemma":0.0008750257,"domain_scores_codex":[0.7357512,0.226424,0.007100715,0.01041426,0.01897071,0.001339139],"domain_scores_gemma":[0.4090675,0.5202784,0.0133076,0.03939696,0.01634058,0.001608963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004023598,0.0002870289,0.008696319,0.001703963,0.001078587,0.0005215513,0.001815646,0.01371812,0.0008377997,0.6283786,0.01916487,0.3233952],"study_design_scores_gemma":[0.0002209772,0.0005214182,0.004045276,0.0005967389,0.0002000628,0.000428119,0.0004207321,0.1091949,0.001855961,0.8599142,0.0224657,0.0001358865],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003168259,0.0005055503,0.9886756,0.0009707652,0.0003230154,0.0004276331,0.0003022019,0.001089718,0.004537291],"genre_scores_gemma":[0.1429514,0.0006537183,0.8469517,0.000878893,0.0006269893,0.004069624,0.0008026622,0.001141108,0.001923978],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1374473,"threshold_uncertainty_score":0.7268993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4184316490265328,"score_gpt":0.5536315416998637,"score_spread":0.1351998926733309,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}