{"id":"W2128379663","doi":"10.6000/1929-6029.2014.03.03.1","title":"Comparison of Methods for Clustered Data Analysis in a Non-Ideal Situation: Results from an Evaluation of Predictors of Yellow Fever Vaccine Refusal in the Global TravEpiNet (GTEN) Consortium","year":2014,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centers for Disease Control and Prevention; National Institutes of Health; Georgetown University; Johns Hopkins University; Kaiser Permanente; Northwestern University; Emory University; Tulane University; University of Southern California","keywords":"Cluster analysis; Statistics; Logistic regression; Random effects model; Generalized estimating equation; Standard error; Odds ratio; Econometrics; Cluster (spacecraft); Sample size determination; Mathematics; Population; Sample (material); Medicine; Computer science; Environmental health; Meta-analysis; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3665573,0.001529247,0.002260666,0.003511028,0.001742365,0.002885554,0.004100326,0.001977713,0.002086644],"category_scores_gemma":[0.6039594,0.001234379,0.006922888,0.004382052,0.002882995,0.003313153,0.005164719,0.00249645,0.000346826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003751509,"about_ca_system_score_gemma":0.006472179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008410838,"about_ca_topic_score_gemma":0.007073795,"domain_scores_codex":[0.4178496,0.5458341,0.01330939,0.0102685,0.0117295,0.001008948],"domain_scores_gemma":[0.2562798,0.6763219,0.01525553,0.03240527,0.01818295,0.001554577],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02288871,0.002542826,0.3672021,0.008429353,0.05291246,0.0008534756,0.019938,0.1366937,0.001433567,0.05581516,0.01520904,0.3160816],"study_design_scores_gemma":[0.00852746,0.01094792,0.2071603,0.003949824,0.007468171,0.001192944,0.008496871,0.6560908,0.003727235,0.0770663,0.01444562,0.0009265593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3219267,0.003138588,0.6616582,0.002121204,0.000559187,0.005635946,0.001616672,0.0008119357,0.002531654],"genre_scores_gemma":[0.5055327,0.000442041,0.4868624,0.0003843675,0.00006760833,0.005023071,0.0009390754,0.0004204831,0.0003281925],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6334428,"threshold_uncertainty_score":0.7811477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2068339951755781,"score_gpt":0.5949867239918685,"score_spread":0.3881527288162904,"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."}}