{"id":"W2168722699","doi":"10.1002/cjs.5550340202","title":"Survival analysis based on the proportional hazards model and survey data","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Weighting; Econometrics; Computer science; Survey data collection; Sampling (signal processing); Statistics; Sampling design; Missing data; Proportional hazards model; Data mining; Mathematics; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.02407331,0.0007811971,0.001467644,0.00307429,0.0006380588,0.001947092,0.002583008,0.001115231,0.005851669],"category_scores_gemma":[0.08625772,0.0006507251,0.001675001,0.004321437,0.002089976,0.002007989,0.002118884,0.002189499,0.000602392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002244253,"about_ca_system_score_gemma":0.003486354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01853026,"about_ca_topic_score_gemma":0.01196202,"domain_scores_codex":[0.9804437,0.01595607,0.0004035024,0.0009829832,0.001578839,0.0006349794],"domain_scores_gemma":[0.9286079,0.06180635,0.002913394,0.004072734,0.002035263,0.0005644088],"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":[0.000506015,0.0001775356,0.04301238,0.0004967991,0.0008223761,0.0007234326,0.001011135,0.2359234,0.0005181747,0.5876196,0.00733685,0.1218524],"study_design_scores_gemma":[0.00016034,0.0002897709,0.009379089,0.0001425096,0.0001968696,0.0003257924,0.0003698046,0.6189193,0.0003472141,0.3616989,0.008092914,0.00007743082],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0273265,0.0007746695,0.9678935,0.001259635,0.0001560431,0.0002787826,0.0005562383,0.0002839349,0.001470698],"genre_scores_gemma":[0.6698697,0.00222038,0.3152321,0.0006763675,0.000395778,0.001766775,0.001715061,0.000149329,0.007974605],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02407331,"threshold_uncertainty_score":0.1273134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2590261621513028,"score_gpt":0.3557593213831456,"score_spread":0.09673315923184278,"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."}}