{"id":"W2072533626","doi":"10.1016/j.jmva.2013.02.008","title":"Estimation of mean squared error of model-based estimators of small area means under a nested error linear regression model","year":2013,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Small area estimation; Mean squared error; Estimator; Statistics; Efficient estimator; Linear model; Minimum mean square error; Conditional expectation; Minimum-variance unbiased estimator","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":[0.02540673,0.0009057964,0.002240431,0.001149355,0.0004664113,0.001534933,0.002653802,0.001907892,0.000957792],"category_scores_gemma":[0.0947832,0.001161486,0.001371764,0.001136554,0.001895606,0.00313979,0.002397452,0.00190007,0.0002543154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166668,"about_ca_system_score_gemma":0.002206888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005194506,"about_ca_topic_score_gemma":0.004125388,"domain_scores_codex":[0.9918394,0.00551657,0.0003981403,0.001098878,0.000921123,0.0002258069],"domain_scores_gemma":[0.9363592,0.05339112,0.002717875,0.004029332,0.003087207,0.0004152303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003275545,0.0001194567,0.007819195,0.0002050394,0.0005086426,0.00006928443,0.0002657314,0.8975775,0.002512759,0.04514424,0.0005904844,0.04486024],"study_design_scores_gemma":[0.00001673995,0.00005298377,0.001022475,0.00001458512,0.00002847415,0.00002931446,0.00001585521,0.9811662,0.0006133697,0.01681654,0.0002067614,0.00001669789],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02860877,0.0001343737,0.9708633,0.00006621109,0.00001626776,0.00001284909,0.00003497795,0.0001099675,0.0001532278],"genre_scores_gemma":[0.4886924,0.000343523,0.5087066,0.0001026268,0.00006812245,0.0001669434,0.0004735048,0.0001842651,0.00126211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02540673,"threshold_uncertainty_score":0.1343653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1169984387393509,"score_gpt":0.3927812466780775,"score_spread":0.2757828079387266,"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."}}