{"id":"W1974553458","doi":"10.1111/j.0006-341x.2004.00232.x","title":"Confidence Interval Estimation of the Intraclass Correlation Coefficient for Binary Outcome Data","year":2004,"lang":"en","type":"article","venue":"Biometrics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intraclass correlation; Confidence interval; Estimator; Biometrics; Mathematics; Statistics; Interval estimation; Point estimation; Binary number; Binary data; Variance (accounting); Correlation; Correlation coefficient; Range (aeronautics); Interval (graph theory); Combinatorics; Computer science; Artificial intelligence","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":[0.0347088,0.001284007,0.001932282,0.005749606,0.0006684376,0.003159555,0.004441652,0.00294446,0.003022833],"category_scores_gemma":[0.3070621,0.0005850838,0.001606857,0.004103961,0.002930829,0.003686203,0.003299603,0.003740547,0.001233531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001099621,"about_ca_system_score_gemma":0.001437186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001444607,"about_ca_topic_score_gemma":0.0008233194,"domain_scores_codex":[0.9817785,0.009764323,0.0009513576,0.001968422,0.005097641,0.0004396955],"domain_scores_gemma":[0.7439771,0.2169708,0.01095705,0.01544937,0.01174009,0.000905476],"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":[0.0003216935,0.0001599974,0.01460348,0.0007109108,0.0005072253,0.0004287605,0.001155551,0.1384033,0.002901872,0.447804,0.004309524,0.3886938],"study_design_scores_gemma":[0.00006196012,0.0001847397,0.005934228,0.0004616874,0.0001668674,0.0007377026,0.0001190494,0.6616204,0.003313486,0.3241364,0.00311593,0.000147614],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004424824,0.0005190907,0.9938852,0.0001096078,0.00002479195,0.00002770087,0.00004744634,0.0001708051,0.0007905133],"genre_scores_gemma":[0.2716702,0.00182082,0.7236955,0.0002598886,0.0002465664,0.0005726925,0.0005773724,0.0002294812,0.0009275216],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0347088,"threshold_uncertainty_score":0.1835598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2188643237565531,"score_gpt":0.4415134958533183,"score_spread":0.2226491720967652,"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."}}