{"id":"W2599685465","doi":"10.20381/ruor-16282","title":"Detecting DIF in polytomous items: An empirical comparison of the ordinal logistic regression, logistic discriminant function analysis, Mantel, and Generalized Mantel-Haenszel procedures.","year":2001,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Polytomous Rasch model; Logistic regression; Discriminant function analysis; Ordered logit; Statistics; Ordinal regression; Mathematics; Econometrics; Ordinal data; Linear discriminant analysis; Item response theory; Psychometrics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1918997,0.001267677,0.001219118,0.006165236,0.0008780111,0.001779495,0.002099091,0.001109524,0.001506263],"category_scores_gemma":[0.5037183,0.0005963802,0.002118664,0.005822841,0.003311655,0.003968617,0.003089256,0.002530144,0.0005008216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001696514,"about_ca_system_score_gemma":0.001923809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001807814,"about_ca_topic_score_gemma":0.002711319,"domain_scores_codex":[0.8164975,0.1606634,0.004843443,0.005587636,0.01180764,0.0006004235],"domain_scores_gemma":[0.394276,0.5554491,0.01991519,0.01682454,0.01251478,0.001020418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003612528,0.000836451,0.4073153,0.001763986,0.004702507,0.0003453896,0.008001073,0.01118392,0.002167568,0.03950283,0.003569957,0.5169985],"study_design_scores_gemma":[0.001124821,0.007895528,0.5836213,0.001504751,0.001819104,0.002548082,0.01007859,0.2788296,0.005661805,0.09010553,0.01599577,0.000815222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.480168,0.003616102,0.5041236,0.001159107,0.0003824262,0.002020794,0.0005747591,0.0006155642,0.007339649],"genre_scores_gemma":[0.7137488,0.000742018,0.2823463,0.000205475,0.00006132331,0.001843156,0.0003347909,0.0001129261,0.0006052032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1918997,"threshold_uncertainty_score":0.9965315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07146919139122176,"score_gpt":0.3402948891894433,"score_spread":0.2688256977982215,"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."}}