{"id":"W2300752603","doi":"10.1002/sim.6909","title":"Type‐II generalized family‐wise error rate formulas with application to sample size determination","year":2016,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Type I and type II errors; Sample size determination; False discovery rate; Null hypothesis; Statistical power; Word error rate; Statistics; Multiple comparisons problem; Statistical hypothesis testing; Computer science; Mathematics; Nominal level; Algorithm; Artificial intelligence; Confidence interval","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002537494,0.0002486322,0.0007043993,0.0001267996,0.00008225445,0.000009387872,0.0002576237,0.0001217717,0.0004580115],"category_scores_gemma":[0.2148865,0.0001469484,0.0000223268,0.0004402573,0.0002407965,0.00005052619,0.00008585716,0.0001587063,0.00004054006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001515774,"about_ca_system_score_gemma":0.00007119902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008033211,"about_ca_topic_score_gemma":0.0001644731,"domain_scores_codex":[0.9972021,0.0004431082,0.001005698,0.000468548,0.0005073348,0.0003732145],"domain_scores_gemma":[0.9275272,0.07105046,0.0002971118,0.0005468799,0.0003661496,0.0002121515],"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":[0.001972231,0.0002625892,0.0008017957,0.0002385979,0.00005877273,0.00004330508,0.0006673766,0.000009896432,0.01645834,0.6491694,0.01613643,0.3141812],"study_design_scores_gemma":[0.003903842,0.001299528,0.003108725,0.0003187944,0.0001020098,0.000002716052,0.000055026,0.001271445,0.0005051743,0.9870271,0.002147274,0.0002583662],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01839591,0.000009295434,0.9777138,0.001487116,0.0003887468,0.001026836,0.0003892387,0.00006972822,0.0005193797],"genre_scores_gemma":[0.04871519,0.00004135689,0.9493572,0.0008065475,0.0003004803,0.0001682006,0.000009137397,0.00005373085,0.0005481518],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3378577,"threshold_uncertainty_score":0.7917268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3034049271407597,"score_gpt":0.5395663056930371,"score_spread":0.2361613785522774,"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."}}