{"id":"W1985969598","doi":"10.1186/1471-2288-11-21","title":"Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: A simulation study","year":2011,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Joseph’s Healthcare Hamilton; Health Sciences Centre; McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Statistics; Intraclass correlation; Estimator; Randomized controlled trial; Type I and type II errors; Context (archaeology); Confidence interval; Statistical power; Generalized estimating equation; Random effects model; Medicine; Gee; Sample size determination; Point estimation; Observational study; Standard error; Mathematics; Outcome (game theory); Meta-analysis; Surgery; Internal medicine","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","metaepi_narrow"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3088385,0.0004459922,0.009668497,0.0009105057,0.0001348431,0.00005023951,0.0005227557,0.0003537054,0.0007166909],"category_scores_gemma":[0.9124405,0.0002547071,0.0005990702,0.0005765499,0.0003267741,0.0000402219,0.0002448293,0.0008790448,0.00004830837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000269789,"about_ca_system_score_gemma":0.0003675598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008319927,"about_ca_topic_score_gemma":0.0009040222,"domain_scores_codex":[0.6584275,0.3341678,0.003563189,0.0009418151,0.0016973,0.001202358],"domain_scores_gemma":[0.2185967,0.7792173,0.0004525836,0.0006316925,0.000332031,0.0007696495],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.3968313,0.004213946,0.01447616,0.0003597614,0.0008173555,0.000486405,0.009397991,0.00006192469,0.0001138425,0.1274823,0.00001898414,0.44574],"study_design_scores_gemma":[0.4441514,0.003407827,0.004952124,0.0004435423,0.0005789171,0.000005759945,0.001139323,0.1985215,0.0005423502,0.3458807,0.00001599673,0.0003606115],"study_design_candidate":"randomized_trial","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07945444,0.00007718521,0.9077222,0.0001215699,0.0003974609,0.01113447,0.000002212372,0.0000790894,0.001011333],"genre_scores_gemma":[0.2341448,0.000008633836,0.7630287,0.00006404176,0.0001093303,0.002524282,0.000001039191,0.00003288447,0.00008630854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6036019,"threshold_uncertainty_score":0.9999905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8018225963297307,"score_gpt":0.692509018615857,"score_spread":0.1093135777138737,"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."}}