{"id":"W2751852067","doi":"10.3758/s13428-020-01355-x","title":"Two-stage maximum likelihood approach for item-level missing data in regression","year":2020,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Missing data; Imputation (statistics); Statistics; Univariate; Regression; Scale (ratio); Regression analysis; Context (archaeology); Econometrics; Restricted maximum likelihood; Mathematics; Computer science; Maximum likelihood; Multivariate statistics","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":[0.04936585,0.00178896,0.003791243,0.00291723,0.001396305,0.002514752,0.007655381,0.003670517,0.005803061],"category_scores_gemma":[0.1375443,0.002290646,0.003434169,0.004700605,0.001883662,0.004051789,0.003818357,0.005896089,0.001702246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001590261,"about_ca_system_score_gemma":0.005169291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005347525,"about_ca_topic_score_gemma":0.005234289,"domain_scores_codex":[0.9556571,0.03726556,0.001366435,0.003040783,0.002092318,0.0005778572],"domain_scores_gemma":[0.9100125,0.0771713,0.003098848,0.005193916,0.004007049,0.0005163616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001212655,0.0005261115,0.02077666,0.001824313,0.001917409,0.0009162758,0.003218767,0.4081646,0.002340715,0.2111988,0.008187303,0.3397164],"study_design_scores_gemma":[0.0002070729,0.0002180517,0.001529728,0.0001301835,0.0001240494,0.0001841862,0.0001220017,0.8963305,0.001002354,0.0958432,0.004217731,0.00009099168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001969967,0.0001629156,0.9969816,0.0001569227,0.00001981452,0.0001146764,0.00009407156,0.0002967718,0.0002032097],"genre_scores_gemma":[0.09083913,0.0002989478,0.9053986,0.0001808878,0.00009097347,0.001239097,0.00060815,0.0002436148,0.001100579],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04936585,"threshold_uncertainty_score":0.2610747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9595380073134077,"score_gpt":0.7275446994992708,"score_spread":0.2319933078141369,"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."}}