{"id":"W4297271369","doi":"10.1002/sim.9549","title":"Substantive model compatible multilevel multiple imputation: A joint modeling approach","year":2022,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Imputation (statistics); Covariate; Computer science; Missing data; Statistics; Multilevel model; Data mining; Econometrics; Mathematics; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02674691,0.0006822515,0.001436476,0.002033247,0.0009659519,0.002606472,0.004540181,0.001610322,0.00499276],"category_scores_gemma":[0.07391784,0.0007935,0.002537342,0.003588967,0.001143918,0.001787071,0.004033864,0.003793443,0.001275453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196505,"about_ca_system_score_gemma":0.004357051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002012807,"about_ca_topic_score_gemma":0.003188683,"domain_scores_codex":[0.9730576,0.02228673,0.0007082682,0.001239343,0.002403194,0.0003048306],"domain_scores_gemma":[0.9521236,0.03402144,0.002824997,0.006873973,0.003479498,0.0006765082],"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":[0.0002108006,0.0001918111,0.01255559,0.0008246595,0.001321257,0.0004718941,0.001286674,0.1072842,0.00136049,0.5324106,0.0168457,0.3252363],"study_design_scores_gemma":[0.0000732151,0.00009494709,0.001895657,0.0002060639,0.0001808447,0.0002983413,0.0001167993,0.5823267,0.0007894535,0.4006787,0.01329072,0.00004866569],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008944612,0.00008711181,0.9979936,0.0003031678,0.00001547186,0.00004609473,0.00008869533,0.0001662778,0.000404987],"genre_scores_gemma":[0.05945329,0.0001968757,0.938701,0.0002369934,0.0000826063,0.0003319641,0.0003705476,0.0001475131,0.0004792623],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02674691,"threshold_uncertainty_score":0.1414529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1922284353356461,"score_gpt":0.4036991178289541,"score_spread":0.211470682493308,"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."}}