{"id":"W2021166956","doi":"10.1016/j.jmva.2008.09.004","title":"Probability density estimation for survival data with censoring indicators missing at random","year":2008,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"National Science Fund for Distinguished Young Scholars; Science Fund for Creative Research Groups; National Natural Science Foundation of China","keywords":"Mathematics; Estimator; Censoring (clinical trials); Statistics; Missing data; Survival function; Nonparametric statistics; Density estimation; Kaplan–Meier estimator; Applied mathematics","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":[0.02982646,0.001304213,0.003860407,0.003927324,0.0009478276,0.002691477,0.004745781,0.002727339,0.003573885],"category_scores_gemma":[0.1439815,0.001533531,0.002906379,0.004445747,0.002995504,0.004749782,0.003050545,0.005110288,0.0008039082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001597938,"about_ca_system_score_gemma":0.002284573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005675031,"about_ca_topic_score_gemma":0.002866972,"domain_scores_codex":[0.9906548,0.006639736,0.0004779493,0.001048101,0.0008582436,0.0003213035],"domain_scores_gemma":[0.8474557,0.1368751,0.004132145,0.007488857,0.003419452,0.0006288054],"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":[0.0005563097,0.0002816419,0.01598196,0.0009707925,0.0008496977,0.0004758443,0.0008970352,0.2470969,0.000778387,0.5581307,0.007677712,0.1663029],"study_design_scores_gemma":[0.00007139058,0.00006661731,0.001881061,0.0001402376,0.0001160594,0.0002638658,0.0001224927,0.6372925,0.0003109351,0.3577008,0.00197997,0.00005398623],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005345236,0.0004175203,0.9934779,0.0001913664,0.00002763673,0.00006334695,0.0001516912,0.0001436659,0.0001816371],"genre_scores_gemma":[0.4122081,0.003887086,0.5710117,0.0003938297,0.0004489264,0.002240444,0.004360268,0.0003419874,0.005107604],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02982646,"threshold_uncertainty_score":0.1577393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1871704705894094,"score_gpt":0.3995046680321129,"score_spread":0.2123341974427035,"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."}}