{"id":"W2080877726","doi":"10.1002/cjs.5550340204","title":"Estimation of regression parameters in missing data problems","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Jerome's University; University of Waterloo","funders":"","keywords":"Covariate; Estimator; Statistics; Mathematics; Missing data; Multivariate statistics; Standard deviation; Regression analysis; Standard error; Conditional expectation; Econometrics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007138503,0.00008639016,0.0002652513,0.0001985248,0.00003622623,0.00003158771,0.0002472064,0.00004967247,0.0000449306],"category_scores_gemma":[0.004595645,0.00007217818,0.00001559364,0.0001481815,0.0001056403,0.00009716413,0.00001308471,0.0001688322,8.407438e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007698071,"about_ca_system_score_gemma":0.0005704231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004402753,"about_ca_topic_score_gemma":0.007980025,"domain_scores_codex":[0.9987536,0.00009849665,0.0006969614,0.0000908794,0.0001782616,0.0001818124],"domain_scores_gemma":[0.9979073,0.001074995,0.0004698313,0.0002236207,0.0001501178,0.0001741139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002881154,0.0001067056,0.00773363,0.000657894,0.00003402444,0.0004228615,0.0006371381,0.003951828,0.0002519952,0.421009,0.03464772,0.5305184],"study_design_scores_gemma":[0.0003256461,0.00009386004,0.005748626,0.0007729072,0.00004272666,0.00004496736,0.00005933906,0.06634855,0.0002482642,0.9259207,0.00028291,0.0001114809],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02591361,0.0001329359,0.972514,0.0001220338,0.0001570448,0.00008188444,0.0005861963,0.000001963368,0.0004903461],"genre_scores_gemma":[0.2676035,0.000004922681,0.7323163,0.00001200378,0.00002238527,2.942927e-7,0.000016829,0.000008718391,0.00001507065],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5304069,"threshold_uncertainty_score":0.6655676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1840471811130979,"score_gpt":0.3665024411091787,"score_spread":0.1824552599960808,"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."}}