{"id":"W3082894259","doi":"10.47302/jsr.2020540101","title":"A comparison of statistical methods for the analysis of binary repeated measures data with additional hierarchical structure","year":2020,"lang":"en","type":"article","venue":"Journal of Statistical Research","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island; University of Ottawa","funders":"","keywords":"Statistics; Mathematics; Random effects model; Autocorrelation; Marginal model; Binary data; Markov chain Monte Carlo; Marginal likelihood; Quasi-likelihood; Count data; Overdispersion; Negative binomial distribution; Bayesian probability; Regression analysis; Poisson distribution; Binary number","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":[0.1173157,0.001105407,0.002245936,0.0027515,0.0007480027,0.00184553,0.002540676,0.001725699,0.003519913],"category_scores_gemma":[0.2888843,0.0007602695,0.002858549,0.003342621,0.001815682,0.002426373,0.001923496,0.003267965,0.0007049791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001461754,"about_ca_system_score_gemma":0.003654656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001521138,"about_ca_topic_score_gemma":0.001866716,"domain_scores_codex":[0.8516812,0.126962,0.004322379,0.005158878,0.01104828,0.0008272484],"domain_scores_gemma":[0.6094716,0.3442991,0.01184815,0.02089278,0.01237477,0.001113679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01181272,0.001880482,0.04471471,0.006021776,0.009167526,0.0008593893,0.003419365,0.05851297,0.01866285,0.06848545,0.009182787,0.7672799],"study_design_scores_gemma":[0.003415826,0.01720646,0.1176083,0.003610549,0.003474303,0.00279022,0.002142171,0.6749378,0.01873856,0.1204569,0.03453672,0.001082087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03727072,0.001766375,0.9563243,0.0003937253,0.0003693014,0.00167403,0.0003855912,0.0008733523,0.0009426058],"genre_scores_gemma":[0.1119316,0.001094691,0.8773463,0.0002524537,0.0001243345,0.007288998,0.0005397552,0.0006048143,0.000817041],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1173157,"threshold_uncertainty_score":0.6204321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4562199842346878,"score_gpt":0.6012562082949747,"score_spread":0.1450362240602869,"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."}}