{"id":"W2072457708","doi":"10.1080/15598608.2013.772830","title":"Bias Correction Methods for Misclassified Covariates in the Cox Model: Comparison of Five Correction Methods by Simulation and Data Analysis","year":2013,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Practice","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Heart, Lung, and Blood Institute; University of Otago; Ryerson University","keywords":"Covariate; Categorical variable; Statistics; Imputation (statistics); Mathematics; Inference; Proportional hazards model; Regression analysis; Regression; Estimation; Data mining; Computer science; Econometrics; Missing data; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02032342,0.0001420538,0.0006249878,0.0001376902,0.0001132187,0.0001161523,0.0001810015,0.0001085188,0.00007235429],"category_scores_gemma":[0.1235151,0.00009312817,0.0000480518,0.0003204581,0.0001781976,0.00051093,0.00004793635,0.0003904277,3.21869e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002001136,"about_ca_system_score_gemma":0.00004181217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004882671,"about_ca_topic_score_gemma":0.000003208022,"domain_scores_codex":[0.9905835,0.007940141,0.000910671,0.0002172392,0.0002036207,0.0001447765],"domain_scores_gemma":[0.7646345,0.2338821,0.0008696483,0.0002009999,0.0003441632,0.00006860302],"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":[0.002318057,0.0004485243,0.0001129118,0.0001188818,0.0005668765,0.000001484253,0.002409102,0.001687623,0.0006489189,0.5863608,0.004169421,0.4011575],"study_design_scores_gemma":[0.0002413316,0.0001890457,0.0002603156,0.00002071352,0.001098322,0.00001729561,0.001967677,0.5236332,0.00008874646,0.4722456,0.0001770714,0.00006067172],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005659028,0.0002057002,0.9980631,0.0002351445,0.0002229694,0.0002912007,0.000132875,0.000004593254,0.0002785175],"genre_scores_gemma":[0.08473697,0.00006160413,0.9150044,0.00008812817,0.00002965414,0.000008601162,0.00001831949,0.000009170313,0.00004320418],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5219456,"threshold_uncertainty_score":0.8838679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2632541689591572,"score_gpt":0.566600147292207,"score_spread":0.3033459783330498,"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."}}