{"id":"W4391138204","doi":"10.1002/sim.10011","title":"Multiple imputation strategies for missing event times in a multi‐state model analysis","year":2024,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; University of Bristol; Medical Research Council Canada; Wellcome Trust; NHS Blood and Transplant","keywords":"Imputation (statistics); Computer science; Missing data; Data mining; Statistics; Machine learning; Mathematics","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":[0.05412706,0.001821669,0.004566985,0.003004597,0.001717452,0.003010223,0.006445237,0.003270973,0.005796203],"category_scores_gemma":[0.1226625,0.001965941,0.004626843,0.0040265,0.001792292,0.004494563,0.00389545,0.006341776,0.001096456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001555574,"about_ca_system_score_gemma":0.003948491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005405979,"about_ca_topic_score_gemma":0.006128465,"domain_scores_codex":[0.9745886,0.01992361,0.001242392,0.002506878,0.001267748,0.0004707261],"domain_scores_gemma":[0.8963637,0.08968614,0.004628217,0.00590559,0.002660688,0.0007556885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004915383,0.0002253141,0.01269894,0.001000164,0.002357799,0.0008697793,0.001100367,0.4910536,0.000630282,0.3290882,0.008690097,0.1517939],"study_design_scores_gemma":[0.00007752144,0.00008468102,0.0006533021,0.0001528153,0.0001635294,0.0001285443,0.00007588702,0.7156194,0.0003510245,0.2794801,0.003150825,0.00006228387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002100541,0.0003239442,0.9965313,0.0003725482,0.00005077352,0.00007276988,0.0001658321,0.000177697,0.0002046876],"genre_scores_gemma":[0.1603576,0.0009862211,0.8327907,0.0007014548,0.000247479,0.001384416,0.001344197,0.0003064075,0.001881448],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05412706,"threshold_uncertainty_score":0.2862546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09443405681533493,"score_gpt":0.4594438165445142,"score_spread":0.3650097597291793,"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."}}