{"id":"W4213422840","doi":"10.21203/rs.3.rs-1374473/v1","title":"Propensity Score Weighting With Survey Weighted Data When Outcomes Are Binary","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre","funders":"National Cancer Institute; National Institute on Aging; Icahn School of Medicine at Mount Sinai","keywords":"Propensity score matching; Weighting; Statistics; Observational study; Context (archaeology); Population; Survey sampling; Average treatment effect; Sample (material); Medicine; Mathematics; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06212937,0.001075248,0.001925235,0.00347853,0.0006537454,0.002672761,0.002486569,0.001662833,0.005696703],"category_scores_gemma":[0.2029494,0.000677224,0.002492687,0.00674345,0.001915012,0.002857664,0.00336521,0.002763369,0.0008547063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001582256,"about_ca_system_score_gemma":0.003096871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003350411,"about_ca_topic_score_gemma":0.001476758,"domain_scores_codex":[0.9028487,0.08199352,0.004726054,0.004323137,0.005461752,0.0006468398],"domain_scores_gemma":[0.8882161,0.07601672,0.01526737,0.01457001,0.005305844,0.0006240116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001446525,0.0004430747,0.08054162,0.003352081,0.004896902,0.0004624685,0.001181778,0.1869665,0.0008731516,0.2279211,0.01959736,0.4723175],"study_design_scores_gemma":[0.001246793,0.001120374,0.03756303,0.001915426,0.001541005,0.0006746398,0.0005703012,0.4128524,0.002771151,0.4837046,0.05572239,0.0003178451],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02303526,0.0009999911,0.9690468,0.0007553463,0.0003357991,0.001860349,0.001297548,0.000334217,0.002334666],"genre_scores_gemma":[0.4347515,0.00195779,0.5510358,0.0008921833,0.0004009432,0.006264941,0.00260002,0.0001885357,0.0019084],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06212937,"threshold_uncertainty_score":0.3285754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5190039026764302,"score_gpt":0.4181116929111608,"score_spread":0.1008922097652693,"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."}}