{"id":"W2904094333","doi":"10.1177/0013164418817801","title":"Centering in Multiple Regression Does Not Always Reduce Multicollinearity: How to Tell When Your Estimates Will Not Benefit From Centering","year":2018,"lang":"en","type":"article","venue":"Educational and Psychological Measurement","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multicollinearity; Independence (probability theory); Regression; Econometrics; Correlation; Regression analysis; Statistics; Context (archaeology); Joint probability distribution; Linear regression; Mathematics; Random variable; Psychology","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":[0.000555052,0.0002398547,0.0003088127,0.00006649254,0.0001973697,0.00007175517,0.0001798696,0.0001042402,0.0002269556],"category_scores_gemma":[0.002578744,0.0001588778,0.00004509485,0.00007319733,0.00008912567,0.0001168971,0.0001024604,0.0001965991,0.00001073507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001077159,"about_ca_system_score_gemma":0.00001427016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000459015,"about_ca_topic_score_gemma":0.00006389268,"domain_scores_codex":[0.9981418,0.00008707026,0.0003660934,0.0006139227,0.0004497797,0.0003413644],"domain_scores_gemma":[0.9985046,0.0006822338,0.0001055619,0.0002558574,0.0002088392,0.0002428518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002611542,0.005733672,0.02353324,0.0002573241,0.0001420376,0.00001877242,0.006382608,0.00007118119,0.7471095,0.03327876,0.003004601,0.1778567],"study_design_scores_gemma":[0.002418699,0.0006603329,0.1297862,0.001363844,0.00005309654,0.00001092595,0.0005371365,0.004142495,0.05461449,0.7998605,0.005662831,0.0008894669],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7580072,0.00006980141,0.2301182,0.009957203,0.000910658,0.0005304268,0.0001633314,0.00004689193,0.0001963112],"genre_scores_gemma":[0.5522336,0.00001340076,0.4469826,0.0003028211,0.0002968748,0.00006197546,0.000007482277,0.00001206228,0.00008915065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7665817,"threshold_uncertainty_score":0.6478848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4401330808779662,"score_gpt":0.4563174100150345,"score_spread":0.01618432913706824,"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."}}