{"id":"W4313857752","doi":"10.1037/met0000537","title":"We need to change how we compute RMSEA for nested model comparisons in structural equation modeling.","year":2023,"lang":"en","type":"article","venue":"Psychological Methods","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Structural equation modeling; Nested set model; Mathematics; Statistics; Applied mathematics; Computer science; Data mining","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2832322,0.002440481,0.004081482,0.009282061,0.004113364,0.01158721,0.009246082,0.004953696,0.009289659],"category_scores_gemma":[0.7561615,0.001709089,0.006525139,0.01188181,0.01104915,0.02384656,0.007745243,0.02207696,0.003787819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004170551,"about_ca_system_score_gemma":0.00689297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007620031,"about_ca_topic_score_gemma":0.01541703,"domain_scores_codex":[0.6652672,0.2745726,0.02337527,0.01358369,0.02182228,0.001378934],"domain_scores_gemma":[0.2836767,0.5970461,0.02109401,0.07023473,0.02486859,0.003079842],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003802786,0.0004413009,0.04858894,0.004366934,0.005026132,0.0004140533,0.009375252,0.006704227,0.001176236,0.2255061,0.1233843,0.5746362],"study_design_scores_gemma":[0.0003249995,0.0008459389,0.02844089,0.008397565,0.001259458,0.0009015684,0.004649173,0.04251271,0.003299142,0.7953766,0.1131984,0.0007934718],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009584147,0.008525519,0.8898138,0.06417385,0.01249447,0.0008534028,0.001000354,0.002359224,0.01119509],"genre_scores_gemma":[0.1120068,0.002302761,0.8590124,0.01702684,0.002549375,0.002773085,0.0006747816,0.002055615,0.001598328],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7167678,"threshold_uncertainty_score":0.8839023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5169415510137839,"score_gpt":0.4988124653351859,"score_spread":0.01812908567859806,"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."}}