{"id":"W2891487057","doi":"10.1002/gepi.22153","title":"Genetic association analysis with pedigrees: Direct inference using the composite likelihood ratio","year":2018,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Frequentist inference; Likelihood function; Inference; Statistics; Likelihood principle; Mathematics; Statistical inference; Bayesian probability; Bayes factor; Bayesian inference; Computer science; Econometrics; Artificial intelligence; Quasi-maximum likelihood; Estimation theory","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02332451,0.001026399,0.001819947,0.00431221,0.0005651122,0.003413235,0.002169641,0.001396982,0.002824124],"category_scores_gemma":[0.137659,0.0009757971,0.001759192,0.003653608,0.003261914,0.004142272,0.003589754,0.003247661,0.0005638973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001180709,"about_ca_system_score_gemma":0.001678665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002629421,"about_ca_topic_score_gemma":0.002097787,"domain_scores_codex":[0.9800249,0.01647105,0.0004353126,0.001519297,0.001410289,0.0001392965],"domain_scores_gemma":[0.9000697,0.09074421,0.003443089,0.003981029,0.001320795,0.0004412585],"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":[0.0002476648,0.0001345481,0.02339328,0.0007324023,0.001324591,0.001221907,0.0006109825,0.1306109,0.001860809,0.5833538,0.003727812,0.2527813],"study_design_scores_gemma":[0.00009069873,0.00006865168,0.001942393,0.00008958377,0.0001265036,0.0006811766,0.00005838051,0.2946674,0.0005696738,0.698297,0.003357529,0.00005094706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002955633,0.0004606383,0.9956136,0.0002506201,0.00002219925,0.00003076702,0.00005177943,0.0000950309,0.00051975],"genre_scores_gemma":[0.2363773,0.002318462,0.7588399,0.0004332594,0.0002519744,0.0003541618,0.0002603505,0.0001182778,0.001046226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02332451,"threshold_uncertainty_score":0.1233532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235082839816757,"score_gpt":0.307064453596918,"score_spread":0.2835561696152423,"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."}}