{"id":"W2038522769","doi":"10.1111/j.1751-5823.2007.00017.x","title":"Methods for Generating Longitudinally Correlated Binary Data","year":2007,"lang":"en","type":"article","venue":"International Statistical Review","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Binary data; Binary number; Computer science; Flexibility (engineering); Contrast (vision); Range (aeronautics); Sample (material); Longitudinal data; Sample size determination; Statistics; Data mining; Algorithm; Mathematics; Econometrics; Artificial intelligence; Arithmetic","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":[0.02137909,0.0005679416,0.001083512,0.002730643,0.0006088527,0.001342621,0.002597049,0.001056442,0.009334268],"category_scores_gemma":[0.0771261,0.0006413186,0.001347927,0.002575288,0.001248576,0.001625865,0.002643309,0.002337185,0.002037253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007583358,"about_ca_system_score_gemma":0.001433745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008770967,"about_ca_topic_score_gemma":0.0009220418,"domain_scores_codex":[0.9890688,0.007939205,0.0004705236,0.0008917893,0.001435559,0.0001941573],"domain_scores_gemma":[0.9564423,0.03254746,0.002827184,0.005001465,0.00277825,0.0004034202],"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":[0.0002993963,0.0001371853,0.006954197,0.000677271,0.0002863048,0.0002032246,0.0005830696,0.04347669,0.001534785,0.5374653,0.00908336,0.3992992],"study_design_scores_gemma":[0.0002178675,0.0001397113,0.002503311,0.0003998482,0.00008565075,0.0003546193,0.0001201054,0.2445536,0.002006447,0.7322802,0.0172422,0.00009644522],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002495008,0.0003456534,0.9955996,0.0002941554,0.00005423811,0.0001499852,0.0002129838,0.0001427758,0.0007054022],"genre_scores_gemma":[0.07812216,0.001023662,0.9149929,0.0002942249,0.0001731186,0.002066286,0.0009530847,0.0001287461,0.002245882],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02137909,"threshold_uncertainty_score":0.1130648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2787789056899614,"score_gpt":0.5783747127488411,"score_spread":0.2995958070588797,"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."}}