{"id":"W1986440280","doi":"10.1002/sim.3276","title":"The performance of different propensity score methods for estimating marginal odds ratios, <i>Statistics in Medicine</i> 2007; <b>26</b>:3078–3094","year":2008,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Institute for Clinical Evaluative Sciences","funders":"Canadian Institutes of Health Research; Ontario Ministry of Health and Long-Term Care","keywords":"Citation; Library science; Odds; Sociology; Medicine; Statistics; Mathematics; Computer science; Logistic regression","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003060166,0.0004095415,0.001173513,0.0002118749,0.0002479575,0.000008181551,0.0004678214,0.0001281699,0.00006115303],"category_scores_gemma":[0.01430753,0.0002637259,0.00002974608,0.0003613047,0.001443767,0.0001066212,0.0001211443,0.0006385849,0.000001435615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002097405,"about_ca_system_score_gemma":0.0001509442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009889554,"about_ca_topic_score_gemma":0.0002218754,"domain_scores_codex":[0.9963815,0.0003447379,0.001637295,0.0004051692,0.0006467756,0.0005845877],"domain_scores_gemma":[0.9886374,0.009389437,0.0007388814,0.0006004172,0.0005226862,0.0001111529],"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":[0.0008931606,0.0004272232,0.0221323,0.00354203,0.00009830869,0.0001412882,0.006440695,0.0002114632,0.007594073,0.7906615,0.05917532,0.1086827],"study_design_scores_gemma":[0.004384464,0.003170782,0.01473248,0.003473547,0.0002101879,0.0001215954,0.0006731837,0.2257846,0.009636201,0.7361155,0.0008865321,0.0008109135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0222688,0.0001966231,0.9747572,0.0003825339,0.0004848087,0.001360968,0.0001110446,0.00009258793,0.000345465],"genre_scores_gemma":[0.07155608,0.0007734376,0.9266934,0.0001699682,0.0002243216,0.0002015238,0.00006148145,0.00007088732,0.000248862],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2255731,"threshold_uncertainty_score":0.9999815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1924724090229699,"score_gpt":0.4680823787825111,"score_spread":0.2756099697595412,"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."}}