{"id":"W3138858220","doi":"10.18637/jss.v097.i07","title":"<b>FamEvent</b>: An <i>R</i> Package for Generating and Modeling Time-to-Event Data in Family Designs","year":2021,"lang":"en","type":"article","venue":"Journal of Statistical Software","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Calgary; Lunenfeld-Tanenbaum Research Institute; Western University","funders":"National Cancer Institute","keywords":"Penetrance; Pedigree chart; Missing data; Computer science; Event (particle physics); Population; Statistics; Covariate; Confidence interval; R package; Data mining; Mathematics; Genetics; Medicine; Biology; Gene","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":[0.008806358,0.002226052,0.00212416,0.001676787,0.0006145296,0.001717066,0.003685464,0.0014952,0.1104449],"category_scores_gemma":[0.03041193,0.001716311,0.00294541,0.001611113,0.000650125,0.001534797,0.001907844,0.002344823,0.03686372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000700606,"about_ca_system_score_gemma":0.001819121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004576425,"about_ca_topic_score_gemma":0.005405818,"domain_scores_codex":[0.9973654,0.001591331,0.0002099375,0.0003509909,0.0003259803,0.0001563291],"domain_scores_gemma":[0.9787124,0.01722163,0.001246415,0.001635323,0.0009152194,0.0002690305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001611896,0.0003420143,0.0186702,0.004728423,0.002718298,0.001057259,0.000879627,0.05469326,0.007523247,0.03766229,0.6520982,0.2180153],"study_design_scores_gemma":[0.001776286,0.0006635687,0.0125643,0.001005195,0.0009860873,0.001691517,0.0001339215,0.3332543,0.01371499,0.07291114,0.5607505,0.0005481897],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.008166296,0.0005028571,0.7219524,0.0004998865,0.0002701617,0.0006817758,0.1200745,0.1428152,0.005037062],"genre_scores_gemma":[0.05183391,0.0007461943,0.7622907,0.0009542759,0.0001821556,0.0064303,0.07879498,0.08765168,0.01111582],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1104449,"threshold_uncertainty_score":0.3694749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05960386585603619,"score_gpt":0.340195600066062,"score_spread":0.2805917342100259,"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."}}