{"id":"W2152325169","doi":"10.1016/j.envres.2014.05.016","title":"Indirect adjustment for multiple missing variables applicable to environmental epidemiology","year":2014,"lang":"en","type":"article","venue":"Environmental Research","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; Statistics Canada; McGill University; Institute of Population and Public Health; University of Toronto; Queen's University; University of Ottawa; Health Canada","funders":"","keywords":"Missing data; Statistics; Proportional hazards model; Environmental epidemiology; Censoring (clinical trials); Weibull distribution; Epidemiology; Confounding; Regression analysis; Cohort study; Hazard ratio; Cohort; Environmental health; Econometrics; Medicine; Demography; Confidence interval; Mathematics; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01478286,0.0009799869,0.0009822451,0.001422457,0.0003184698,0.0007316194,0.002209312,0.0007107808,0.00555226],"category_scores_gemma":[0.09152476,0.0005383377,0.001857793,0.001154602,0.0009094342,0.0008971444,0.002363783,0.002162671,0.0007890133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008181051,"about_ca_system_score_gemma":0.003030819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00283104,"about_ca_topic_score_gemma":0.004478482,"domain_scores_codex":[0.9923344,0.005472474,0.0002385085,0.0005359576,0.001283736,0.0001348922],"domain_scores_gemma":[0.973345,0.01970346,0.002315065,0.002466935,0.001952139,0.0002174861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002875394,0.000200126,0.03483175,0.001202732,0.001718683,0.0003326176,0.0007411215,0.2132533,0.004454539,0.1920153,0.007005528,0.5439567],"study_design_scores_gemma":[0.0002235011,0.0003373029,0.01567231,0.0005067004,0.00040006,0.0004172729,0.0001116509,0.7068892,0.004956764,0.2448584,0.02553268,0.00009420195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001636708,0.00008228881,0.9976539,0.0000960607,0.00001612192,0.00008287088,0.00006807236,0.0001372898,0.0002267841],"genre_scores_gemma":[0.07358139,0.0005093096,0.9216582,0.0001726903,0.0001038181,0.00160717,0.0004184224,0.0002035932,0.001745409],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01478286,"threshold_uncertainty_score":0.07818019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1887007708574004,"score_gpt":0.4465999730553326,"score_spread":0.2578992021979322,"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."}}