{"id":"W4361269722","doi":"10.1080/19466315.2023.2197402","title":"Application of Group Sequential Methods to the 2-in-1 Design and Its Extensions for Interim Monitoring","year":2023,"lang":"en","type":"article","venue":"Statistics in Biopharmaceutical Research","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Michael Smith Health Research BC","keywords":"Interim; Interim analysis; Group (periodic table); Adaptive design; Research design; Computer science; Reliability engineering; Medicine; Statistics; Risk analysis (engineering); Medical physics; Mathematics; Randomized controlled trial; Clinical trial; Engineering; Internal medicine; Political science; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.06816719,0.001932297,0.002411449,0.001475698,0.0009851176,0.001876239,0.002424626,0.002904593,0.01281355],"category_scores_gemma":[0.1127054,0.0009307811,0.002880679,0.001392619,0.004021771,0.002770493,0.002996183,0.004847438,0.00177209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173115,"about_ca_system_score_gemma":0.003555672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000399345,"about_ca_topic_score_gemma":0.0004842537,"domain_scores_codex":[0.9324703,0.0574041,0.001714489,0.003742428,0.004033733,0.0006348826],"domain_scores_gemma":[0.9104943,0.06905787,0.005707239,0.0106167,0.003366561,0.0007573105],"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":[0.003252427,0.0004402265,0.004424471,0.001673714,0.000704862,0.0004715479,0.001235967,0.05617302,0.004165452,0.6635667,0.006255529,0.2576361],"study_design_scores_gemma":[0.001679117,0.00557075,0.001959481,0.000394348,0.0003913269,0.0005487209,0.0001182512,0.2216938,0.003750608,0.7365499,0.02717143,0.0001723068],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003443603,0.0002685259,0.9927619,0.0003974352,0.0001728947,0.001034152,0.0001101638,0.0002068264,0.001604417],"genre_scores_gemma":[0.1285477,0.0005015747,0.8590554,0.00104661,0.0003304915,0.008481753,0.0001697868,0.0001287393,0.001737891],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06816719,"threshold_uncertainty_score":0.3605068,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9038046754759503,"score_gpt":0.7565153356159264,"score_spread":0.1472893398600239,"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."}}