{"id":"W4318024824","doi":"10.1002/sim.9658","title":"Propensity score matching after multiple imputation when a confounder has missing data","year":2023,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Propensity score matching; Causal inference; Missing data; Imputation (statistics); Confounding; Statistics; Observational study; Average treatment effect; Matching (statistics); Estimator; Computer science; Confidence interval; Inference; Covariate; Econometrics; Mathematics; Artificial intelligence","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":[0.001178013,0.0001800069,0.0003605257,0.0001785645,0.00009070049,0.00004022013,0.0002963105,0.00007351695,0.0001458393],"category_scores_gemma":[0.005262186,0.0001506139,0.000008978387,0.0002466688,0.0002634933,0.0002205848,0.0002822157,0.0003121948,0.00002565013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009476246,"about_ca_system_score_gemma":0.00008239574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002322698,"about_ca_topic_score_gemma":0.0004855058,"domain_scores_codex":[0.9983574,0.00009351783,0.0004906564,0.0003585631,0.0003961574,0.0003036839],"domain_scores_gemma":[0.997313,0.001660911,0.0001637832,0.0006535743,0.0001336102,0.00007508329],"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":[0.000671279,0.0004404022,0.06816714,0.004271942,0.0002381503,0.00408502,0.05490792,0.0001836979,0.01571045,0.346765,0.3171068,0.1874521],"study_design_scores_gemma":[0.0005300693,0.00006250145,0.01246602,0.0006207263,0.00003354047,0.00001109726,0.000401085,0.01150764,0.0001077168,0.9736603,0.0004176612,0.0001816702],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03081481,0.00003658205,0.9666271,0.0009003276,0.000188319,0.0005056597,0.0002067964,0.0003626144,0.0003577975],"genre_scores_gemma":[0.4986424,0.00002508472,0.5001764,0.0002708847,0.0001112946,0.00003372346,0.0005222901,0.0000433781,0.000174542],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6268952,"threshold_uncertainty_score":0.6299708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4066710686130003,"score_gpt":0.4617133532211096,"score_spread":0.05504228460810928,"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."}}