{"id":"W3005846352","doi":"10.1111/bmsp.12201","title":"Can we disregard the whole model? Omnibus non‐inferiority testing for <i>R</i> <sup>2</sup> in multi‐variable linear regression and in ANOVA","year":2020,"lang":"en","type":"article","venue":"British Journal of Mathematical and Statistical Psychology","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Statistics; Null hypothesis; Statistical hypothesis testing; Outcome (game theory); Type I and type II errors; Multiple comparisons problem; Linear regression; Bayesian probability; Econometrics; Regression analysis; Linear model; Analysis of variance; Statistical power; Variable (mathematics); Computer science; Mathematics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2569647,0.001957929,0.005287142,0.001975104,0.001396806,0.005108776,0.005103603,0.004599224,0.008619613],"category_scores_gemma":[0.5446261,0.001174679,0.005400529,0.001981208,0.01147979,0.008808415,0.004160023,0.006526973,0.001151019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00232774,"about_ca_system_score_gemma":0.00447798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001296556,"about_ca_topic_score_gemma":0.001294842,"domain_scores_codex":[0.775158,0.1806249,0.008285982,0.01610148,0.01763317,0.002196429],"domain_scores_gemma":[0.2095204,0.7469386,0.01335523,0.02505293,0.003763552,0.00136925],"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":[0.0161914,0.001397626,0.05821596,0.004259289,0.01205524,0.003434179,0.009159283,0.04462786,0.005766436,0.446466,0.0127598,0.3856671],"study_design_scores_gemma":[0.001095301,0.004289346,0.01684815,0.0007210572,0.001517277,0.001225625,0.00134968,0.1710982,0.003754645,0.7916268,0.00614156,0.0003322799],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1167272,0.001704597,0.8656868,0.006068457,0.001236538,0.0008783725,0.0004002215,0.0004247933,0.006873023],"genre_scores_gemma":[0.7287282,0.000799007,0.2639321,0.002344168,0.0006755305,0.001660065,0.0003223421,0.000394545,0.001144073],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2569647,"threshold_uncertainty_score":0.9162949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.165318622558917,"score_gpt":0.426819047784887,"score_spread":0.2615004252259699,"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."}}