{"id":"W4390021842","doi":"10.5964/meth.8285","title":"Which robust regression technique is appropriate under violated assumptions? A simulation study","year":2023,"lang":"en","type":"article","venue":"Methodology","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Robust regression; Statistics; Ordinary least squares; Regression; Regression analysis; Heteroscedasticity; Outlier; Mathematics; Mean squared error; Regression diagnostic; Econometrics; Monte Carlo method; Linear regression; Polynomial regression","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004912432,0.000216857,0.0005165929,0.0002325119,0.0001831917,0.00001656257,0.0001622832,0.000263979,0.0001586459],"category_scores_gemma":[0.006655393,0.0001703894,0.00006224562,0.0007921765,0.00004414309,0.0000821286,0.0001506327,0.0003630696,0.00005616678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005053949,"about_ca_system_score_gemma":0.00002850108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001884247,"about_ca_topic_score_gemma":0.00002538476,"domain_scores_codex":[0.9950793,0.003327881,0.0004917685,0.0005133205,0.0002213195,0.0003663686],"domain_scores_gemma":[0.9904819,0.008521454,0.0001913245,0.0004977162,0.0002241262,0.00008344464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00133889,0.002901434,0.002160721,0.0007104059,0.0007941312,0.0001395139,0.0121176,0.3506301,0.1100098,0.3410794,0.003780983,0.1743371],"study_design_scores_gemma":[0.0004649329,0.0001927736,0.001262068,0.00003320118,0.0000761073,0.000005489221,0.0004256418,0.09276474,0.001252694,0.9031906,0.0001294929,0.0002022467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02617703,0.000009731539,0.9714647,0.0003186409,0.0002105846,0.001054824,0.00001456153,0.0004817024,0.0002682158],"genre_scores_gemma":[0.126906,0.000009848021,0.8719631,0.00008111614,0.00005646415,0.0002224789,0.00001096802,0.00004803799,0.0007019415],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5621113,"threshold_uncertainty_score":0.7967608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.590566386328184,"score_gpt":0.5569675912452756,"score_spread":0.03359879508290842,"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."}}