{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0264091,0.001090408,0.002633501,0.002133952,0.0008982508,0.002594399,0.003910364,0.002283293,0.00229648],"category_scores_gemma":[0.1005078,0.001069502,0.001235649,0.002626999,0.003977919,0.003377928,0.00302078,0.003406937,0.0004586767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002021181,"about_ca_system_score_gemma":0.002332015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006870201,"about_ca_topic_score_gemma":0.003637148,"domain_scores_codex":[0.9821454,0.01316768,0.0004580313,0.001609466,0.002066361,0.0005530716],"domain_scores_gemma":[0.9346474,0.05788189,0.003521579,0.002012975,0.001672169,0.0002639354],"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":[0.0001009448,0.00006902532,0.002978665,0.0002888122,0.000275836,0.0001954598,0.0001688941,0.4301312,0.0005630377,0.5244744,0.001570265,0.03918349],"study_design_scores_gemma":[0.00002822662,0.00001325339,0.0004044219,0.00005416409,0.00002703104,0.00003205455,0.00001957813,0.842841,0.0003203013,0.1555115,0.000724198,0.00002413265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003818803,0.0002398096,0.9949976,0.0002431696,0.00002118365,0.00002215668,0.00003136451,0.00006314578,0.0005628573],"genre_scores_gemma":[0.5063511,0.001346054,0.4862586,0.0005986198,0.0002790554,0.0005105879,0.0003844714,0.0001598608,0.004111595],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0264091,"threshold_uncertainty_score":0.1396664,"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."}}