{"id":"W4377092643","doi":"10.1093/ije/dyad064","title":"Key considerations for designing, conducting and analysing a cluster randomized trial","year":2023,"lang":"en","type":"article","venue":"International Journal of Epidemiology","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"Collaboration for Leadership in Applied Health Research and Care - Greater Manchester; Medical Research Council; National Institute for Health and Care Research; National Institute on Handicapped Research","keywords":"Randomization; Randomized controlled trial; Sample size determination; Cluster randomised controlled trial; Cluster (spacecraft); Cluster analysis; Identification (biology); Sample (material); Inference; Computer science; Statistics; Data mining; Medicine; Artificial intelligence; Mathematics; Surgery","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.5804737,0.004328823,0.01084058,0.007651154,0.006038898,0.01940831,0.008813275,0.02477842,0.0130536],"category_scores_gemma":[0.7966321,0.006841276,0.007536166,0.009374382,0.01775463,0.01299996,0.006298608,0.02868915,0.01003729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01393211,"about_ca_system_score_gemma":0.05400712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004937876,"about_ca_topic_score_gemma":0.007450541,"domain_scores_codex":[0.207414,0.6689798,0.074536,0.01050249,0.03590756,0.002660155],"domain_scores_gemma":[0.1248306,0.76131,0.03029221,0.02900425,0.04623431,0.008328653],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.005630979,0.0005142213,0.002735246,0.04980423,0.002598005,0.001515601,0.01367266,0.01180687,0.002111413,0.2817515,0.1139994,0.5138599],"study_design_scores_gemma":[0.005825915,0.003426007,0.005184365,0.07836847,0.002425119,0.003447503,0.00327444,0.01987083,0.003623366,0.5155041,0.3576079,0.001442075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002235856,0.02821568,0.682966,0.1863122,0.01159424,0.07282967,0.00135524,0.001298656,0.01319246],"genre_scores_gemma":[0.01079263,0.004660218,0.9148982,0.01246113,0.002508363,0.05331558,0.0001456347,0.0002646035,0.0009536893],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4195263,"threshold_uncertainty_score":0.5173507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4140149211849274,"score_gpt":0.5205296786459321,"score_spread":0.1065147574610047,"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."}}