{"id":"W4386878567","doi":"10.1002/sim.9899","title":"Addressing missing data in the estimation of time‐varying treatments in comparative effectiveness research","year":2023,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Missing data; Inverse probability weighting; Imputation (statistics); Weighting; Confounding; Statistics; Inverse probability; Covariate; Econometrics; Computer science; Mathematics; Medicine; Posterior probability; Propensity score matching; Bayesian probability","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006176893,0.0001129606,0.0004015633,0.0005147202,0.00005226788,0.000009978951,0.0003671461,0.00005004877,0.00001840856],"category_scores_gemma":[0.007224138,0.00008088804,0.000005110927,0.001255062,0.0002911367,0.0001318231,0.0001339878,0.0003833651,0.000005707376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001693498,"about_ca_system_score_gemma":0.00006221633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003154903,"about_ca_topic_score_gemma":0.0001473949,"domain_scores_codex":[0.9974968,0.001005737,0.000467611,0.0002386035,0.0005333386,0.0002579532],"domain_scores_gemma":[0.9851077,0.01418737,0.0001182891,0.000484072,0.00008180651,0.00002080991],"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":[0.001245009,0.002563562,0.04280587,0.007565953,0.0002049347,0.002554444,0.1810833,0.01262333,0.05070772,0.3455729,0.01997769,0.3330952],"study_design_scores_gemma":[0.00101484,0.0001801454,0.01887089,0.003710536,0.00001563126,0.000003081703,0.001610887,0.1800001,0.001316037,0.79318,0.000004959937,0.00009283982],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4563033,0.0002246032,0.53523,0.000520769,0.0001027727,0.002712848,0.00035322,0.0001384908,0.00441392],"genre_scores_gemma":[0.8814613,0.00003821154,0.1180323,0.000008792105,0.0000173459,0.00006117365,0.0003497207,0.00001467,0.00001655022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4476071,"threshold_uncertainty_score":0.864849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6914773159287642,"score_gpt":0.6378653717663129,"score_spread":0.0536119441624513,"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."}}