{"id":"W2135248568","doi":"10.1080/15305058.2011.602810","title":"A Generalized Logistic Regression Procedure to Detect Differential Item Functioning Among Multiple Groups","year":2011,"lang":"en","type":"article","venue":"International Journal of Testing","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Differential item functioning; Logistic regression; Completeness (order theory); Statistics; Item response theory; Mathematics; Set (abstract data type); Extension (predicate logic); Differential (mechanical device); Flexibility (engineering); Regression; Psychology; Psychometrics; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02482094,0.002602845,0.002291553,0.004490952,0.001013135,0.001029098,0.003077067,0.001272232,0.008413578],"category_scores_gemma":[0.07430244,0.0008670276,0.003508095,0.005101036,0.001142049,0.001776825,0.004033432,0.003338331,0.002410328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006076544,"about_ca_system_score_gemma":0.002807016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002813347,"about_ca_topic_score_gemma":0.002551824,"domain_scores_codex":[0.9686525,0.02626705,0.0008563373,0.001977835,0.00176201,0.0004842472],"domain_scores_gemma":[0.9692172,0.02014408,0.00224015,0.005483858,0.002655143,0.0002595033],"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":[0.000886876,0.0005574807,0.04813306,0.001302951,0.004338192,0.001413936,0.002094596,0.03195885,0.0092157,0.06153109,0.01909071,0.8194765],"study_design_scores_gemma":[0.001353886,0.004456861,0.09473854,0.0008849564,0.002583298,0.005267627,0.001964333,0.5710397,0.01331999,0.2407903,0.06259857,0.001001944],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01327661,0.0001588738,0.9826073,0.0003830783,0.00007637838,0.0007876079,0.0005554376,0.001446726,0.0007079623],"genre_scores_gemma":[0.1334035,0.0003626586,0.8568074,0.0002607273,0.0001022761,0.004892964,0.001102277,0.0003475309,0.00272061],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02482094,"threshold_uncertainty_score":0.1312672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.548040852468272,"score_gpt":0.4478112341211973,"score_spread":0.1002296183470748,"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."}}