{"id":"W1974232043","doi":"10.1002/cjs.10136","title":"A resampling approach to estimate variance components of multilevel models","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Wilfrid Laurier University","funders":"","keywords":"Resampling; Estimator; Variance (accounting); Statistics; Computer science; Multilevel model; Econometrics; Cluster (spacecraft); Variance components; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.03789815,0.001064139,0.002204816,0.005024024,0.001296659,0.00183484,0.003247838,0.001551351,0.00368615],"category_scores_gemma":[0.1407493,0.001025005,0.003331991,0.003444146,0.001814557,0.001776575,0.002624953,0.003029332,0.0004660526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001545385,"about_ca_system_score_gemma":0.001997214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.012129,"about_ca_topic_score_gemma":0.01079242,"domain_scores_codex":[0.9546314,0.0400603,0.0007354078,0.001376349,0.00284482,0.0003517075],"domain_scores_gemma":[0.9212392,0.06371599,0.003257062,0.007302962,0.004059086,0.0004256939],"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":[0.0002387741,0.0002656999,0.01102937,0.0006004749,0.002713176,0.0004355622,0.001640403,0.2654564,0.001481797,0.4863968,0.006703734,0.223038],"study_design_scores_gemma":[0.000108806,0.0001751831,0.002345394,0.000162256,0.0002374503,0.0001132731,0.0001438942,0.7310843,0.0007244308,0.2591605,0.005666075,0.000078258],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003138034,0.0001388936,0.9959628,0.0001379075,0.00004759374,0.0001120883,0.00004676083,0.0001039707,0.000312004],"genre_scores_gemma":[0.1264403,0.0002823554,0.8709674,0.0001836267,0.0001495786,0.001036393,0.00025398,0.000111173,0.0005752124],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03789815,"threshold_uncertainty_score":0.2004269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.203346326797722,"score_gpt":0.3821604670666834,"score_spread":0.1788141402689615,"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."}}