{"id":"W2103371988","doi":"10.1002/sim.5705","title":"The performance of different propensity score methods for estimating marginal hazard ratios","year":2012,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":995,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Work & Health; Institute for Clinical Evaluative Sciences; Public Health Ontario; University of Toronto","funders":"Canadian Institutes of Health Research; Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences; Heart and Stroke Foundation of Canada","keywords":"Propensity score matching; Covariate; Statistics; Odds ratio; Estimator; Matching (statistics); Medicine; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002238949,0.0001514908,0.0003968481,0.00005268499,0.0001149006,0.000005728927,0.0001813139,0.00004535697,0.00002308958],"category_scores_gemma":[0.006526079,0.00008779509,0.00001731552,0.00009666391,0.0002996201,0.00008154345,0.00006211945,0.0002099996,5.209366e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007045359,"about_ca_system_score_gemma":0.00002840429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005186673,"about_ca_topic_score_gemma":0.00001888416,"domain_scores_codex":[0.998678,0.0001365724,0.0005378662,0.0001177051,0.0002152649,0.0003146451],"domain_scores_gemma":[0.9950841,0.004075878,0.0002993941,0.0002889437,0.0001929272,0.00005876641],"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":[0.0001415097,0.0001310219,0.02683964,0.001189853,0.00003550294,0.000001166249,0.00178377,0.00001416456,0.005966098,0.7812556,0.003408749,0.1792329],"study_design_scores_gemma":[0.0009979375,0.0009844513,0.012969,0.00101758,0.0001281161,0.00001373897,0.0002930119,0.08898605,0.02950362,0.8643796,0.0004199635,0.0003068998],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06839165,0.00009420794,0.9301739,0.0001203102,0.0002656203,0.0007133104,0.00001670286,0.00003677284,0.0001874982],"genre_scores_gemma":[0.1917724,0.00004180599,0.807808,0.00002542271,0.0001250119,0.0001122633,0.00001057819,0.00001759673,0.00008695062],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.178926,"threshold_uncertainty_score":0.7812798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.220207531187187,"score_gpt":0.4904911441960751,"score_spread":0.2702836130088881,"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."}}