{"id":"W2029653161","doi":"10.1198/016214504000000340","title":"Robust Analysis of Generalized Linear Mixed Models","year":2004,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Manitoba","funders":"","keywords":"Generalized linear mixed model; Outlier; Likelihood function; Mathematics; Estimator; Generalized linear model; M-estimator; Applied mathematics; Maximum likelihood; Restricted maximum likelihood; Monte Carlo method; Algorithm; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.01714263,0.002608221,0.003612576,0.003230133,0.0007532793,0.002770006,0.003332834,0.002064142,0.002797415],"category_scores_gemma":[0.05977127,0.001155756,0.004306815,0.002884334,0.002184624,0.001876953,0.003236396,0.003346945,0.0008617891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001595052,"about_ca_system_score_gemma":0.002554933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003187072,"about_ca_topic_score_gemma":0.002197272,"domain_scores_codex":[0.9797513,0.01480069,0.0006302373,0.002007838,0.002436062,0.0003738839],"domain_scores_gemma":[0.9721452,0.02267848,0.001876162,0.001589552,0.001535917,0.0001747403],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001724779,0.00006742213,0.001314584,0.0007937775,0.001321176,0.0002894563,0.0002467095,0.5667938,0.002164811,0.2711205,0.003016948,0.1526983],"study_design_scores_gemma":[0.00002645778,0.00007606048,0.0004587481,0.00006400264,0.0001092708,0.00008909077,0.00002414562,0.8767803,0.0008435966,0.117872,0.003602699,0.00005358949],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007468359,0.0003418473,0.9983245,0.00007932101,0.00002558588,0.00002681074,0.00005135787,0.0001508653,0.0002528533],"genre_scores_gemma":[0.1244133,0.002821834,0.8677351,0.0002858937,0.0003503588,0.0009951292,0.0009042463,0.000335864,0.002158196],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01714263,"threshold_uncertainty_score":0.09066004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1074256277736992,"score_gpt":0.40104898200332,"score_spread":0.2936233542296208,"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."}}