{"id":"W2046657333","doi":"10.1002/cjs.11249","title":"Multiple imputation for the analysis of incomplete compound variables","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Imputation (statistics); Missing data; Estimator; Multivariate statistics; Statistics; Econometrics; Mathematics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001071537,0.00008947423,0.0003838106,0.0002572082,0.00009187975,0.00004774312,0.0002143525,0.00004039712,0.0000554985],"category_scores_gemma":[0.008963725,0.00006320086,0.00008118192,0.0003646539,0.0001469372,0.00004513472,0.000007397329,0.0001047159,5.740442e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009143831,"about_ca_system_score_gemma":0.0008615597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002157923,"about_ca_topic_score_gemma":0.01454674,"domain_scores_codex":[0.9988754,0.00009924477,0.0005788093,0.00006903696,0.0001963129,0.0001812358],"domain_scores_gemma":[0.9905656,0.007391498,0.0004911628,0.0001386177,0.001067806,0.0003453073],"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":[0.00003985993,0.00002061116,0.004038725,0.00006011654,0.0008952072,0.00002553628,0.0009358779,0.0006397411,0.00002056741,0.9573854,0.01385742,0.02208097],"study_design_scores_gemma":[0.00049354,0.0001500103,0.006500535,0.00002728093,0.001634047,0.0000159669,0.0004658397,0.08821245,0.00002202763,0.9003868,0.001996949,0.00009461677],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001323301,0.00007185616,0.9957654,0.0001517658,0.0002456883,0.0001190134,0.00222876,0.000001859788,0.00009231651],"genre_scores_gemma":[0.2767197,0.000002911409,0.7231541,0.0000388256,0.00005101869,0.00000190437,0.00001251894,0.000008401693,0.00001066968],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2753963,"threshold_uncertainty_score":0.9993842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1270308782037829,"score_gpt":0.3559818079120106,"score_spread":0.2289509297082276,"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."}}