{"id":"W4366411838","doi":"10.1002/cjs.11773","title":"Bayesian instrumental variable estimation in linear measurement error models","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Prior probability; Instrumental variable; Estimator; Bayes' theorem; Mathematics; Applied mathematics; Bayes estimator; Statistics; Mean squared error; Linear model; Bias of an estimator; Variance (accounting); Minimum-variance unbiased estimator; Bayesian probability","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001852416,0.0001441718,0.0003491008,0.000438417,0.00009063097,0.00006054899,0.0002053304,0.00007684326,0.0002955067],"category_scores_gemma":[0.003620858,0.000134923,0.00003685593,0.000477731,0.00007296714,0.0001541994,0.00001231613,0.0002829513,0.00001622087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003954214,"about_ca_system_score_gemma":0.001404398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001199859,"about_ca_topic_score_gemma":0.006648297,"domain_scores_codex":[0.9980122,0.0001547775,0.0008290433,0.000128985,0.0004906448,0.000384299],"domain_scores_gemma":[0.9982209,0.0004781473,0.0002884745,0.0001578637,0.0003778348,0.0004768058],"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":[0.0000171196,0.00003252696,0.0008397235,0.000123829,0.00004129864,0.0004660149,0.0006705738,0.002986261,0.00003473179,0.9458868,0.01600635,0.03289475],"study_design_scores_gemma":[0.0003119751,0.00008048149,0.0007715767,0.000151373,0.00002589673,0.00003397389,0.0001514231,0.2697113,0.00001941385,0.7284245,0.0002071755,0.0001109099],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00105236,0.00001534871,0.9968396,0.0001821271,0.0004702519,0.0001269093,0.0004181956,0.000009456497,0.0008856927],"genre_scores_gemma":[0.2093322,0.000005020534,0.7904989,0.00005046457,0.00004296043,0.000003083669,0.000008745162,0.00002029131,0.00003832875],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.266725,"threshold_uncertainty_score":0.5502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1156410796696769,"score_gpt":0.336877311477307,"score_spread":0.2212362318076301,"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."}}