{"id":"W2765291517","doi":"10.1080/10705511.2017.1374187","title":"An Investigation of the Alignment Method With Polytomous Indicators Under Conditions of Partial Measurement Invariance","year":2017,"lang":"en","type":"article","venue":"Structural Equation Modeling A Multidisciplinary Journal","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"University of Connecticut; U.S. Department of Education","keywords":"Polytomous Rasch model; Measurement invariance; Skew; Econometrics; Computer science; Factor analysis; Statistical power; Statistics; Mathematics; Structural equation modeling; Confirmatory factor analysis; Item response theory; Psychometrics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008608704,0.0001671386,0.0003376064,0.0003700015,0.00160311,0.0002385471,0.001256426,0.00008054807,0.00003871814],"category_scores_gemma":[0.006355347,0.00009083461,0.0001293785,0.0005452839,0.0003003574,0.0007735693,0.0001832357,0.0002991398,6.183084e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000102708,"about_ca_system_score_gemma":0.0003464874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001192135,"about_ca_topic_score_gemma":0.00002466701,"domain_scores_codex":[0.9948589,0.001066225,0.001133913,0.0003427507,0.002372225,0.0002260366],"domain_scores_gemma":[0.994122,0.001057737,0.002799024,0.0009303016,0.0009325519,0.0001583974],"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":[0.0001046697,0.00002041253,0.2099559,0.000006896168,0.00005541437,0.000001164474,0.002070059,0.7548319,0.02231164,0.001706471,0.000004321701,0.008931091],"study_design_scores_gemma":[0.0005099477,0.0001334255,0.3349665,0.00007080157,0.00003435967,0.00003706255,0.001534997,0.5612063,0.00384583,0.09756757,1.933044e-7,0.0000930532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6108527,0.00002615022,0.3880108,0.0005940769,0.0003368309,0.0001376646,0.00001023882,0.00000640291,0.00002513617],"genre_scores_gemma":[0.8944387,0.00000308606,0.1054244,0.00001476408,0.000097039,0.000005046678,0.000001953047,0.000009266612,0.000005696005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.283586,"threshold_uncertainty_score":0.9996967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4263957672306052,"score_gpt":0.4729737817399195,"score_spread":0.04657801450931426,"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."}}