{"id":"W2112912314","doi":"10.1080/02664763.2013.789098","title":"Multivariate models for correlated count data","year":2013,"lang":"en","type":"article","venue":"Journal of Applied Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of British Columbia","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Overdispersion; Count data; Poisson distribution; Multivariate statistics; Statistics; Negative binomial distribution; Mathematics; Zero-inflated model; Poisson regression; Econometrics; Population; Demography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008139829,0.0001957586,0.000534724,0.00006906482,0.00009382674,0.00005877382,0.0004764585,0.0001010591,0.00009260073],"category_scores_gemma":[0.001351042,0.0001535725,0.00004408355,0.00007685804,0.00006917169,0.0002642405,0.0001073933,0.0003039329,0.00001092298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005686944,"about_ca_system_score_gemma":0.0001078272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007632652,"about_ca_topic_score_gemma":0.000002147265,"domain_scores_codex":[0.9981175,0.00003692985,0.0009497672,0.0002188979,0.0003670015,0.0003099035],"domain_scores_gemma":[0.9943149,0.003594963,0.0007643151,0.0004611974,0.0006688298,0.000195797],"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":[0.000162145,0.0001439185,4.945024e-7,0.0001001401,0.0001128884,0.000008228017,0.0002376479,0.002402643,0.0006434317,0.9181662,0.04196116,0.03606111],"study_design_scores_gemma":[0.0008443724,0.00008399447,0.000005715564,0.00002253578,0.0001144341,0.00001033456,0.0000885486,0.3558231,0.00004500498,0.6416265,0.001214681,0.0001208392],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002046286,0.00002711622,0.9962214,0.00006452348,0.000285818,0.000568656,0.001557195,0.00001888956,0.001051776],"genre_scores_gemma":[0.02434921,0.00003328125,0.975081,0.0001213801,0.0001408186,0.00002121208,0.00005215298,0.00004998346,0.0001510147],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3534204,"threshold_uncertainty_score":0.6262506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2020919523255862,"score_gpt":0.4319513065614795,"score_spread":0.2298593542358933,"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."}}