{"id":"W4225377897","doi":"10.1002/pds.5446","title":"Alternative analytic and matching approaches for the prevalent new‐user design: A simulation study","year":2022,"lang":"en","type":"article","venue":"Pharmacoepidemiology and Drug Safety","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Janssen Pharmaceuticals; Johnson and Johnson; National Institutes of Health","keywords":"Propensity score matching; Matching (statistics); Weighting; Medicine; Statistics; Relative risk; Cohort; Efficiency; Econometrics; Mathematics; Internal medicine; Confidence interval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005475622,0.000176088,0.0003437183,0.00005385848,0.0005579834,0.000009344138,0.000170465,0.00002746181,0.00005158402],"category_scores_gemma":[0.001013542,0.0001254777,0.00004889055,0.00007986704,0.00008329655,0.0001216982,0.0002565581,0.000318672,3.819366e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006163284,"about_ca_system_score_gemma":0.00002781632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006431351,"about_ca_topic_score_gemma":0.000009389917,"domain_scores_codex":[0.9974169,0.001506684,0.0004019403,0.0003463761,0.0001014124,0.0002267276],"domain_scores_gemma":[0.9796233,0.01987009,0.0002391959,0.0001787591,0.00002607672,0.00006257537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002023735,0.000616505,0.01091877,0.0001705531,0.0008558587,0.000006976151,0.02129495,0.7625373,0.0001104127,0.1498532,0.004574154,0.04703762],"study_design_scores_gemma":[0.0008699267,0.0001529295,0.0008183168,0.000006230303,0.0002432895,0.000007000215,0.001647129,0.4144672,0.00006242435,0.5805909,0.0009816225,0.0001530651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02566496,0.0006527488,0.9696631,0.001702869,0.00008209219,0.002064978,0.00001755324,0.0001045581,0.00004716562],"genre_scores_gemma":[0.9656791,0.0001447255,0.03284208,0.0004949677,0.00008846149,0.0004594752,0.000004601868,0.00002031979,0.0002662347],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9400142,"threshold_uncertainty_score":0.5116832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3953143985526518,"score_gpt":0.4816124235455468,"score_spread":0.08629802499289496,"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."}}