{"id":"W2056465578","doi":"10.1016/j.spl.2010.10.020","title":"Shrinkage strategy in stratified random sample subject to measurement error","year":2010,"lang":"en","type":"article","venue":"Statistics & Probability Letters","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Shrinkage; Estimator; Shrinkage estimator; Mathematics; Statistics; Monte Carlo method; Stratified sampling; Sample (material); Econometrics; Minimum-variance unbiased estimator; Bias of an estimator","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":[0.02716011,0.001028577,0.002394703,0.001125057,0.0006068459,0.001215903,0.002409582,0.002058092,0.002555391],"category_scores_gemma":[0.06344627,0.001445989,0.001338753,0.001270385,0.001881393,0.002372106,0.00281369,0.001846614,0.0008552351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008342452,"about_ca_system_score_gemma":0.001837021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001292507,"about_ca_topic_score_gemma":0.001146704,"domain_scores_codex":[0.9904528,0.006912473,0.0004162956,0.0009114549,0.001017846,0.0002890558],"domain_scores_gemma":[0.97555,0.0177054,0.001191619,0.003339452,0.001761119,0.0004523422],"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":[0.0009795686,0.0002090926,0.005402644,0.000523778,0.0006494171,0.0006136901,0.0007696502,0.1745537,0.006745696,0.6035587,0.007108953,0.1988851],"study_design_scores_gemma":[0.0001266014,0.0001427909,0.001190521,0.00005433662,0.0001603169,0.0002081633,0.00004423978,0.788258,0.002600586,0.2045439,0.002628426,0.00004217534],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006556507,0.0001101843,0.992531,0.0001745518,0.00004189447,0.0000559349,0.00003339809,0.0001319967,0.0003645397],"genre_scores_gemma":[0.2612611,0.0005848833,0.7294234,0.0004762356,0.0002553064,0.001087363,0.0005144029,0.0002847488,0.006112493],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02716011,"threshold_uncertainty_score":0.1436381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1162389841826321,"score_gpt":0.3581135926900388,"score_spread":0.2418746085074067,"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."}}