{"id":"W2083103060","doi":"10.1002/cjs.10139","title":"Duration analysis in longitudinal studies with intermittent observation times and losses to followup","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Censoring (clinical trials); Spell; Econometrics; Statistics; Inverse probability weighting; Inverse probability; Parametric statistics; Weighting; Proportional hazards model; Panel data; Estimation; Regression analysis; Event study; Event (particle physics); Demography; Mathematics; Medicine; Economics; Geography; Propensity score matching; Sociology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.07628579,0.000470616,0.001448834,0.002851471,0.001091345,0.001704158,0.002152695,0.001335293,0.003679299],"category_scores_gemma":[0.209745,0.0004989597,0.001425485,0.004892219,0.001949628,0.002265503,0.002559736,0.002260516,0.0002366743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231076,"about_ca_system_score_gemma":0.001920801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008400766,"about_ca_topic_score_gemma":0.007294338,"domain_scores_codex":[0.9651505,0.02799506,0.001919358,0.002677487,0.001667234,0.0005902494],"domain_scores_gemma":[0.6569098,0.290523,0.03138153,0.01597867,0.003515503,0.001691588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001112433,0.0001867642,0.4678818,0.001979169,0.003662848,0.001393842,0.00390988,0.06551184,0.0008086361,0.2132444,0.006329733,0.2339788],"study_design_scores_gemma":[0.0001740731,0.0009401584,0.2288882,0.001360721,0.001786553,0.0008222517,0.002289459,0.2726273,0.001034819,0.4677409,0.0221539,0.0001815651],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2124533,0.01134923,0.7670304,0.003342778,0.0003280789,0.0003391504,0.002560192,0.0002218394,0.002375089],"genre_scores_gemma":[0.8810636,0.003048619,0.1088518,0.0006028669,0.0004783796,0.001371686,0.002088562,0.00007611245,0.002418416],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07628579,"threshold_uncertainty_score":0.4034426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1755610268300437,"score_gpt":0.3700639636713978,"score_spread":0.1945029368413541,"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."}}