{"id":"W2484604119","doi":"10.1177/0962280216658920","title":"Propensity score matching and complex surveys","year":2016,"lang":"en","type":"article","venue":"Statistical Methods in Medical Research","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":192,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research","keywords":"Propensity score matching; Covariate; Statistics; Confounding; Matching (statistics); Sample size determination; Medicine; Population; Demography; Econometrics; Mathematics; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.07793386,0.0009244516,0.001968686,0.003656563,0.0009540851,0.002544535,0.002075485,0.001901881,0.00504913],"category_scores_gemma":[0.229308,0.0008725738,0.001479813,0.008054586,0.003381456,0.003986802,0.003436729,0.003330928,0.0005042357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002387582,"about_ca_system_score_gemma":0.004043958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003656917,"about_ca_topic_score_gemma":0.002344375,"domain_scores_codex":[0.903447,0.08604067,0.002587368,0.003303126,0.004150601,0.0004712125],"domain_scores_gemma":[0.8604512,0.1092232,0.01368039,0.01270252,0.003237427,0.0007053124],"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":[0.0002174308,0.0001579506,0.02149084,0.0009660525,0.0009873833,0.0001672903,0.0008921417,0.05454461,0.00032091,0.7105243,0.006167427,0.2035636],"study_design_scores_gemma":[0.0001956273,0.0002010691,0.007529591,0.0004340218,0.0001387977,0.0001823967,0.0001732423,0.111176,0.0003700685,0.862163,0.01736752,0.00006868951],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00897838,0.001423602,0.9850831,0.001786951,0.000132206,0.0005031292,0.0002204509,0.000171871,0.001700406],"genre_scores_gemma":[0.2370485,0.004521309,0.7524403,0.001106572,0.0004716995,0.002355793,0.0006960278,0.0001188567,0.001240896],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07793386,"threshold_uncertainty_score":0.4121585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7553058634596144,"score_gpt":0.6754228526511649,"score_spread":0.0798830108084495,"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."}}