{"id":"W1548332406","doi":"10.1002/per.860","title":"Modern Regression Methods that can Substantially Increase Power and Provide a more Accurate Understanding of Associations","year":2011,"lang":"en","type":"article","venue":"European Journal of Personality","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Institute on Aging","keywords":"Outlier; Heteroscedasticity; Regression; Normality; Missing data; Regression analysis; Sample size determination; Econometrics; Psychology; Sample (material); Linear regression; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004389849,0.0001458572,0.0003882618,0.00006829289,0.0001089108,0.00002010689,0.000150061,0.00003005011,0.00004259147],"category_scores_gemma":[0.002392376,0.0001061386,0.0001185236,0.0000801826,0.0001409893,0.0001813147,0.00006421291,0.0002676647,1.64635e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008916392,"about_ca_system_score_gemma":0.00007326851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001965943,"about_ca_topic_score_gemma":0.00001069163,"domain_scores_codex":[0.9970316,0.001790606,0.0005470705,0.0001500334,0.0003056551,0.0001749863],"domain_scores_gemma":[0.9976552,0.0008332118,0.0009612429,0.0001529445,0.0002119842,0.0001853742],"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":[0.00271378,0.001536047,0.01664882,0.0009178311,0.001473347,0.001434314,0.2025232,0.00002825686,0.03445015,0.6701061,0.001144451,0.06702368],"study_design_scores_gemma":[0.00185149,0.000454346,0.03088323,0.0005682359,0.0004112733,0.0001375177,0.006465176,0.001515125,0.002292356,0.9549238,0.00009546527,0.0004020063],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1519708,0.000112205,0.8448182,0.000138443,0.00006036255,0.00008167703,0.00006627614,0.000009636079,0.002742394],"genre_scores_gemma":[0.5328447,0.00001611644,0.4670414,0.00003081508,0.00001784898,2.002324e-7,5.430628e-7,0.00001647303,0.0000318598],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3808739,"threshold_uncertainty_score":0.4328208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4063817560702697,"score_gpt":0.4559161575341374,"score_spread":0.04953440146386767,"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."}}