{"id":"W1974830949","doi":"10.1002/sim.4435","title":"Global hypothesis testing for high‐dimensional repeated measures outcomes","year":2011,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Center for Advancing Translational Sciences; National Institute of Dental and Craniofacial Research; National Institute on Drug Abuse; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute on Alcohol Abuse and Alcoholism","keywords":"Sample size determination; Type I and type II errors; Covariate; False discovery rate; Multiple comparisons problem; Computer science; Inference; Univariate; Statistical power; Statistical hypothesis testing; Statistics; Statistical inference; Nominal level; Multivariate statistics; Mathematics; Machine learning; Artificial intelligence; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004790977,0.0002904917,0.00110298,0.0001000271,0.00008314819,0.00000778704,0.0002961107,0.0001656616,0.00053323],"category_scores_gemma":[0.603422,0.000214622,0.00005166339,0.0003779209,0.0004351925,0.00002757536,0.00007269686,0.0002062486,0.00001233925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000119014,"about_ca_system_score_gemma":0.00008440169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003812705,"about_ca_topic_score_gemma":0.0001423927,"domain_scores_codex":[0.9964074,0.0004892072,0.001507115,0.0004814269,0.0006536271,0.0004611964],"domain_scores_gemma":[0.882557,0.1159717,0.0003831456,0.0004527068,0.0004568805,0.0001786267],"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":[0.0004053773,0.0003515308,0.0430536,0.0002455932,0.0001820515,0.0001309946,0.0002343112,0.000003011991,0.00007431789,0.8411524,0.02212009,0.09204667],"study_design_scores_gemma":[0.002273584,0.0004944113,0.07469875,0.0002061575,0.0002043903,0.000006478888,0.00004421374,0.0003296752,0.00006490529,0.9214402,0.00002536993,0.0002118327],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007512093,0.0000366042,0.9830608,0.0004197504,0.001458,0.001068561,0.001555817,0.0001634654,0.004724849],"genre_scores_gemma":[0.05857496,0.000003977922,0.9405084,0.0004328595,0.0002196524,0.00007985719,0.000006346236,0.00004101258,0.0001328795],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5986311,"threshold_uncertainty_score":0.8752032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7088825096546587,"score_gpt":0.5518508889249891,"score_spread":0.1570316207296696,"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."}}