{"id":"W2072546393","doi":"10.3102/1076998606298037","title":"Point Estimates and Confidence Intervals for Variable Importance in Multiple Linear Regression","year":2007,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada; Carleton University","funders":"","keywords":"Statistics; Confidence interval; Linear regression; Variable (mathematics); Regression analysis; Mathematics; Measure (data warehouse); Variance (accounting); Regression; Linear model; Regression diagnostic; Econometrics; Bayesian multivariate linear regression; Computer science; Data mining","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":[0.07495872,0.001590294,0.002788023,0.007605434,0.0007629839,0.003755733,0.00519698,0.003518416,0.004078543],"category_scores_gemma":[0.5423942,0.0008657075,0.002264155,0.008394957,0.003408265,0.005265206,0.003548037,0.006080374,0.001113406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00136324,"about_ca_system_score_gemma":0.0009546171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001477968,"about_ca_topic_score_gemma":0.0006072588,"domain_scores_codex":[0.9037481,0.07285565,0.003434014,0.00540918,0.01379096,0.0007620077],"domain_scores_gemma":[0.3562389,0.6088876,0.0126756,0.01260328,0.009004243,0.0005903803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007811586,0.000162148,0.01603771,0.003091754,0.001329879,0.0005310364,0.00113316,0.1121917,0.0009386392,0.4459245,0.009297959,0.4085804],"study_design_scores_gemma":[0.0001537447,0.0004538293,0.01397875,0.002433802,0.0006047304,0.001151929,0.0003909432,0.2659588,0.002476458,0.6989138,0.0132062,0.0002769418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008676873,0.01328766,0.97414,0.0005393049,0.0002662684,0.0001007049,0.0003400439,0.000432421,0.002216737],"genre_scores_gemma":[0.4579352,0.01441266,0.5204049,0.000489629,0.001586763,0.001186252,0.001846602,0.0006977693,0.001440202],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07495872,"threshold_uncertainty_score":0.3964244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1748694814327777,"score_gpt":0.4944659832462644,"score_spread":0.3195965018134866,"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."}}