{"id":"W2073524117","doi":"10.1080/03610926.2012.687067","title":"Conditional Score Tests for Heteroscedasticity in the Two-Way Error Components Model","year":2014,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Heteroscedasticity; Score test; Econometrics; Statistics; Mathematics; Score; Asymptotic distribution; Statistic; Lagrange multiplier; Statistical hypothesis testing; Estimator; Mathematical optimization","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":[0.01654357,0.0007624915,0.001685997,0.002434378,0.0005834444,0.001550538,0.00240416,0.0009910743,0.006173124],"category_scores_gemma":[0.105029,0.0003302465,0.001511364,0.003851454,0.002204783,0.003165212,0.003026227,0.002132416,0.0008997755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000579046,"about_ca_system_score_gemma":0.00286828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278835,"about_ca_topic_score_gemma":0.001119796,"domain_scores_codex":[0.983182,0.01143973,0.0007728015,0.001639485,0.00240212,0.0005638833],"domain_scores_gemma":[0.8974768,0.0864249,0.005011237,0.006373468,0.00380258,0.0009110796],"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":[0.0005078625,0.0003332368,0.07297831,0.0004536293,0.001563628,0.0006051307,0.0008987035,0.09724241,0.002977814,0.5497185,0.00418045,0.2685404],"study_design_scores_gemma":[0.000139713,0.0007855274,0.04105878,0.00009783125,0.0002466959,0.0005070281,0.0005507773,0.5445281,0.004188812,0.4029453,0.004774367,0.0001771302],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0796064,0.0001557193,0.9166356,0.0002075527,0.0000407416,0.0001073216,0.0004306314,0.000290928,0.002525076],"genre_scores_gemma":[0.8172429,0.0002468681,0.1779813,0.0001550139,0.0001367378,0.0004294302,0.001551303,0.0001183149,0.002138108],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01654357,"threshold_uncertainty_score":0.08749181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1848906580046299,"score_gpt":0.407821683438203,"score_spread":0.2229310254335731,"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."}}