{"id":"W1596246169","doi":"10.1186/1471-2156-7-24","title":"LRTae: improving statistical power for genetic association with case/control data when phenotype and/or genotype misclassification errors are present","year":2006,"lang":"en","type":"article","venue":"BMC Genetics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institutes of Health; National Institute of Mental Health; University of Toronto","keywords":"Statistical power; Sample size determination; Statistics; Locus (genetics); Type I and type II errors; Genotype; Statistical hypothesis testing; Likelihood-ratio test; Genetic association; Statistic; Computer science; Data mining; Biology; Genetics; Mathematics; Single-nucleotide polymorphism","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":[0.129596,0.001421662,0.003413697,0.004157268,0.0009005097,0.002250772,0.003676685,0.003047044,0.01251923],"category_scores_gemma":[0.3405155,0.001088848,0.004984313,0.00352144,0.003219444,0.00315075,0.003503535,0.004652035,0.001611651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006868525,"about_ca_system_score_gemma":0.00166669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007894205,"about_ca_topic_score_gemma":0.0009195576,"domain_scores_codex":[0.8673397,0.1109868,0.00447402,0.007988257,0.008393707,0.0008174679],"domain_scores_gemma":[0.5451803,0.4118335,0.00885425,0.02492283,0.008160513,0.001048571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003316964,0.0007285295,0.05842682,0.003331409,0.007213433,0.001281214,0.002069165,0.05323455,0.01261692,0.03376303,0.0189265,0.8050914],"study_design_scores_gemma":[0.003133115,0.003412807,0.05004212,0.0009740275,0.002406413,0.003439961,0.0004193749,0.7703691,0.02298455,0.1093818,0.03289853,0.0005381287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01563444,0.0004103064,0.9792616,0.0004043225,0.0002233236,0.0005181283,0.0003609684,0.002190507,0.0009964363],"genre_scores_gemma":[0.1779395,0.0002091144,0.816415,0.0005045922,0.0001518479,0.002245526,0.0006255966,0.001036251,0.0008726124],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.129596,"threshold_uncertainty_score":0.6853771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02770822057752536,"score_gpt":0.2765934262312881,"score_spread":0.2488852056537628,"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."}}