{"id":"W2043447175","doi":"10.1016/j.jmva.2013.09.003","title":"Marginal regression analysis of clustered failure time data with a cure fraction","year":2013,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Estimator; Statistics; Marginal model; Estimating equations; Fraction (chemistry); Regression; Proportional hazards model; Regression analysis; Hazard ratio; Applied mathematics; Survival function; Hazard; Confidence interval","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":[0.01248603,0.00135231,0.002382366,0.002673953,0.0005822398,0.001480147,0.003368266,0.001773209,0.004116111],"category_scores_gemma":[0.04776462,0.001025832,0.00273297,0.00193643,0.00159797,0.002253,0.001979966,0.002796179,0.0007296393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001131804,"about_ca_system_score_gemma":0.001521573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005854913,"about_ca_topic_score_gemma":0.00375741,"domain_scores_codex":[0.9961768,0.002188292,0.000132579,0.0007005393,0.0004837569,0.0003180392],"domain_scores_gemma":[0.9674521,0.02472199,0.002339091,0.003135057,0.001828399,0.0005233064],"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":[0.0008779868,0.0002301806,0.01243667,0.0003637197,0.0006632785,0.0002789882,0.0006198499,0.7713493,0.004621479,0.125306,0.002919675,0.08033301],"study_design_scores_gemma":[0.00001482317,0.00004275484,0.002442346,0.00001904371,0.00006070844,0.00005555391,0.00003237586,0.9753318,0.000509793,0.02103943,0.0004198065,0.00003165738],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0565405,0.000347512,0.9415647,0.0002434881,0.0000337178,0.00004678013,0.000196975,0.0005474984,0.0004787865],"genre_scores_gemma":[0.8594536,0.000610196,0.1328937,0.00013841,0.000177781,0.0002610673,0.001044402,0.0005417993,0.00487908],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01248603,"threshold_uncertainty_score":0.06603318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02003713000080463,"score_gpt":0.2987926363546233,"score_spread":0.2787555063538186,"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."}}