{"id":"W2073184828","doi":"10.1198/sbr.2010.09050","title":"Estimating Simultaneous Confidence Intervals for Multiple Contrasts of Proportions by the Method of Variance Estimates Recovery","year":2010,"lang":"en","type":"article","venue":"Statistics in Biopharmaceutical Research","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation","keywords":"Confidence interval; Statistics; Confidence distribution; Variance (accounting); Mathematics; Robust confidence intervals; Multivariate statistics; CDF-based nonparametric confidence interval; Binomial (polynomial); Credible interval; Sample size determination; Coverage probability; Econometrics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01963577,0.0002332909,0.0008799218,0.0001470866,0.000159012,0.00005150513,0.0008197225,0.0002485778,0.0007979075],"category_scores_gemma":[0.7412772,0.0001728111,0.0001131096,0.0005514314,0.001958916,0.00005695298,0.0002594519,0.001543304,0.000006828994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005327829,"about_ca_system_score_gemma":0.0002877389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008736319,"about_ca_topic_score_gemma":0.00004977831,"domain_scores_codex":[0.9940453,0.001612694,0.0020132,0.0005351364,0.00103972,0.0007539035],"domain_scores_gemma":[0.4659784,0.5314168,0.0004540879,0.0005522505,0.001398727,0.0001997347],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001513084,0.001180898,0.000339741,0.002151596,0.0001822503,0.00003251697,0.0002655649,0.0002237148,0.1568189,0.6739522,0.008536827,0.1548028],"study_design_scores_gemma":[0.0008565094,0.0002557912,0.00003939797,0.0001810023,0.00004955918,0.000006556198,0.00004198571,0.3082813,0.03961306,0.6503761,0.0001777292,0.000121014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002060337,0.00003943504,0.9845256,0.0003402237,0.0005282601,0.002076452,0.01021146,0.00002450273,0.0001937289],"genre_scores_gemma":[0.1380852,0.00001915763,0.8613299,0.00003411377,0.00008785498,0.0002912817,0.00001881065,0.00004098252,0.00009277407],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7216414,"threshold_uncertainty_score":0.8736527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5664644995065378,"score_gpt":0.6641135688704715,"score_spread":0.0976490693639337,"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."}}