{"id":"W2061106845","doi":"10.1002/hec.969","title":"Country specific cost comparisons from multinational clinical trials using empirical Bayesian shrinkage estimation: the Canadian ASSENT-3 economic analysis","year":2005,"lang":"en","type":"article","venue":"Health Economics","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; St. Joseph’s Healthcare Hamilton; McMaster University; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Bayes' theorem; Estimation; Bayesian probability; Econometrics; Multinational corporation; Inference; Causal inference; Shrinkage estimator; Bayesian inference; Statistics; MEDLINE; Economics; Mathematics; Computer science; Mean squared error; Minimum-variance unbiased estimator","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":[0.1368953,0.001410371,0.003842113,0.003973442,0.001126677,0.002804328,0.001922907,0.001316586,0.002907328],"category_scores_gemma":[0.2904438,0.0005928116,0.004891573,0.006500696,0.001356814,0.002005722,0.002735476,0.002903587,0.0001347366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009789634,"about_ca_system_score_gemma":0.01184148,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2829701,"about_ca_topic_score_gemma":0.3870002,"domain_scores_codex":[0.8601727,0.1268775,0.003142424,0.001571373,0.007346564,0.0008894409],"domain_scores_gemma":[0.8415865,0.1339867,0.007498431,0.009742678,0.006555154,0.0006306447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01124029,0.0002500733,0.06224849,0.005176634,0.04476348,0.0007122785,0.00118638,0.2865562,0.0004032364,0.1298335,0.01911081,0.4385186],"study_design_scores_gemma":[0.008351353,0.001462278,0.1233631,0.005370616,0.03301293,0.0007234676,0.00102193,0.4999645,0.001415638,0.2715586,0.05309038,0.0006651332],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.313887,0.1052376,0.4917317,0.02615,0.0009733179,0.006799341,0.008938357,0.0005669539,0.04571575],"genre_scores_gemma":[0.8523476,0.009447212,0.1277472,0.00216585,0.0002014775,0.002343082,0.003154547,0.0001679162,0.002425116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7170299,"threshold_uncertainty_score":0.7239802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7220569113690556,"score_gpt":0.5814935485690143,"score_spread":0.1405633628000413,"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."}}