{"id":"W1873375728","doi":"10.1002/sim.6314","title":"EM for regularized zero‐inflated regression models with applications to postoperative morbidity after cardiac surgery in children","year":2014,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Montreal Children's Hospital","funders":"National Center for Advancing Translational Sciences; National Institute of Environmental Health Sciences; National Heart, Lung, and Blood Institute; National Institute of Diabetes and Digestive and Kidney Diseases; National Cancer Institute; National Institutes of Health; Charles H. Hood Foundation","keywords":"Poisson regression; Count data; Poisson distribution; Expectation–maximization algorithm; Regression; Medicine; Likelihood function; Statistics; Overdispersion; Regression analysis; Zero-inflated model; Cardiac surgery; Model selection; Computer science; Econometrics; Mathematics; Maximum likelihood; Surgery; Population","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":[0.01108691,0.001200559,0.001883834,0.001282181,0.0005411872,0.0009037141,0.003052462,0.001706043,0.002115655],"category_scores_gemma":[0.03284344,0.001045764,0.001753903,0.001498019,0.001451671,0.001768566,0.001901668,0.002583931,0.0005467563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001186972,"about_ca_system_score_gemma":0.001818859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004559302,"about_ca_topic_score_gemma":0.003358519,"domain_scores_codex":[0.9962919,0.00285522,0.0001524161,0.0003856479,0.0002002706,0.0001146452],"domain_scores_gemma":[0.981215,0.01626994,0.0009793604,0.0005697227,0.0007808842,0.0001850911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001264235,0.00004840989,0.002365843,0.000184577,0.0001629948,0.0001471724,0.0001257206,0.8929557,0.0004220118,0.06306124,0.001865644,0.03853429],"study_design_scores_gemma":[0.00001472082,0.00001791673,0.0001542331,0.00001396779,0.00001017087,0.00002573093,0.00001000036,0.9808611,0.0001271301,0.01811987,0.0006355397,0.000009508493],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002949188,0.0002111736,0.996277,0.0002119173,0.00001717269,0.00002171341,0.00004654863,0.0001062193,0.0001588997],"genre_scores_gemma":[0.1719491,0.001091532,0.8214486,0.0004437677,0.0002475972,0.0007043567,0.0008197812,0.00029255,0.003002661],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01108691,"threshold_uncertainty_score":0.05863386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05210787311159458,"score_gpt":0.3740036816381332,"score_spread":0.3218958085265386,"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."}}